CN109218538A - Mobile terminal screen control method, mobile terminal and computer readable storage medium - Google Patents
Mobile terminal screen control method, mobile terminal and computer readable storage medium Download PDFInfo
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- CN109218538A CN109218538A CN201811440876.2A CN201811440876A CN109218538A CN 109218538 A CN109218538 A CN 109218538A CN 201811440876 A CN201811440876 A CN 201811440876A CN 109218538 A CN109218538 A CN 109218538A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
- H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
- H04M1/724—User interfaces specially adapted for cordless or mobile telephones
- H04M1/72448—User interfaces specially adapted for cordless or mobile telephones with means for adapting the functionality of the device according to specific conditions
- H04M1/72454—User interfaces specially adapted for cordless or mobile telephones with means for adapting the functionality of the device according to specific conditions according to context-related or environment-related conditions
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/14—Digital output to display device ; Cooperation and interconnection of the display device with other functional units
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M2250/00—Details of telephonic subscriber devices
- H04M2250/12—Details of telephonic subscriber devices including a sensor for measuring a physical value, e.g. temperature or motion
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Abstract
The invention discloses a kind of mobile terminal screen autocontrol method, mobile terminal and computer readable storage mediums to belong to field of mobile terminals applied to the mobile terminal with Processing with Neural Network module.It include: acquisition ultrasonic signal；The collected ultrasonic signal is pre-processed, feature vector is generated；Status categories are obtained using the Processing with Neural Network module forecast analysis described eigenvector；Screen state is controlled according to the status categories.Through the embodiment of the present invention, the discrimination and accuracy rate that can greatly improve ultrasonic distance measurement make user realize that the automatic bright screen of mobile terminal screen, go out screen in making and receiving calls, improve user experience.
Description
Technical field
The present invention relates to field of mobile terminals, in particular to a kind of mobile terminal screen autocontrol method, mobile terminal
And computer readable storage medium.
Background technique
Currently, mobile terminal becomes increasingly popular, more and more using the user of mobile terminal, and user routine use is mobile eventually
End is also more and more frequent, so that mobile terminal has become one of essential mobile device of user.
Ultrasonic technology is quite mature in industrial circle application.Currently, industrial ultrasonic measuring distance technology mainly divides
Based on amplitude and based on the two methods of phase.It as its name suggests, based on amplitude is propagated in air gradually according to ultrasonic wave
The characteristic of decaying, based on phase be by compare send and receive time difference of pulse acoustical signal estimate shelter away from
From.
Currently, screen has obtained the application of scale in the terminal comprehensively, and shields comprehensively and apply in the terminal
The development of ultrasonic wave on mobile terminals is pushed, for example, how to realize using ultrasonic wave in user's making and receiving calls mobile whole
The automatic bright screen of end screen, go out screen.In field of mobile terminals, the simple distance measuring method of both the above cannot all complete ranging, because
Small, the system complex for the system space of mobile terminal, mobile terminal can receive mobile terminal internal structure conduction and outer simultaneously
The ultrasonic wave of portion's shelter reflection, both ultrasonic waves, which are overlapped mutually, produces extremely complex scene, and ultrasonic wave is caused to identify
Rate and accuracy rate are low, and user experience is low.
How to realize that the automatic bright screen of mobile terminal screen, go out screen in user's making and receiving calls using ultrasonic wave, is one
Urgent problem at present.
Summary of the invention
In view of this, a kind of mobile terminal screen autocontrol method, mobile terminal and meter provided in an embodiment of the present invention
Calculation machine readable storage medium storing program for executing can greatly improve ultrasound applied to the mobile terminal with Processing with Neural Network module
Away from discrimination and accuracy rate, so that user is realized that the automatic bright screen of mobile terminal screen, go out screen in making and receiving calls, improve user
Experience.
It is as follows that the present invention solves technical solution used by above-mentioned technical problem:
According to an aspect of an embodiment of the present invention, the method that a kind of mobile terminal screen provided automatically controls, application
In the mobile terminal with Processing with Neural Network module, comprising:
Acquire ultrasonic signal；
The collected ultrasonic signal is pre-processed, feature vector is generated；
Status categories are obtained using the Processing with Neural Network module forecast analysis described eigenvector；
Screen state is controlled according to the status categories.
In a possible design, the acquisition ultrasonic signal, including structural vibration be conducted through come direct sound wave and
Pass through the reflected reflected sound in head.
It is described that the collected ultrasonic signal is pre-processed, comprising: to acquisition in a possible design
The ultrasonic signal arrived carries out following at least one pretreatment: framing, spectrum analysis, characteristic vector pickup.
In a possible design, described eigenvector reaction is shelter in approach and far from mobile terminal front
When collected ultrasonic wave changing rule.
It is described to be obtained using the Processing with Neural Network module forecast analysis described eigenvector in a possible design
To status categories, comprising:
The mobile terminal uses the Processing with Neural Network module forecast analysis described eigenvector, detection approach movement
With the generation far from movement；
The mobile terminal is acted using the Processing with Neural Network module according to approach and the inspection of the generation far from movement
It surveys as a result, obtaining status categories.
In a possible design, the mobile terminal is using spy described in the Processing with Neural Network module forecast analysis
Levy vector, the movement of detection approach and the generation far from movement, comprising:
The mobile terminal is extracted the spy formed by ultrasonic signal using Processing with Neural Network module extraction
The feature for levying a period of time course in vector, the characteristic value that the feature calculation of different periods in this section of time history is obtained are constituted
Feature vector, analytic learning form the changing rule of this section of time history, obtain the network mould of the Processing with Neural Network module
Type weight obtains the neural network model of the Processing with Neural Network module；
The neural network model of the Processing with Neural Network module analyzes what the ultrasonic signal preprocessing module generated
Described eigenvector, the movement of detection approach and separate generation.
In a possible design, the mobile terminal using the Processing with Neural Network module according to approach movement and
The testing result of generation far from movement, obtains status categories, comprising:
The mobile terminal uses prediction after the Processing with Neural Network module analysis described eigenvector to have approach movement
When generation, judge that status categories are close；
The mobile terminal uses prediction after the Processing with Neural Network module analysis described eigenvector to have separate movement
When generation, judge status categories to be separate；
The mobile terminal is predicted to move without approach after using the Processing with Neural Network module analysis described eigenvector
When making or occurring far from movement, judge that status categories are constant for state.
It is described to control screen state according to the status categories, comprising: the status categories in a possible design
When to approach, screen movement of going out is executed；When the status categories are separate, bright screen movement is executed；The status categories be state not
When change, keep screen state constant.
Other side according to an embodiment of the present invention, a kind of mobile terminal provided, comprising: memory, processor and
It is stored in the computer program that can be run on the memory and on the processor, the computer program is by the processing
Device realizes the step of method that the mobile terminal screen provided in an embodiment of the present invention automatically controls when executing.
Other side according to an embodiment of the present invention, a kind of computer readable storage medium provided, the computer
The program of the method for mobile terminal screen automatic control is stored on readable storage medium storing program for executing, the mobile terminal screen automatically controls
The program of method realize what the mobile terminal screen provided in an embodiment of the present invention automatically controlled when being executed by processor
The step of method.
Compared with the relevant technologies, a kind of mobile terminal screen autocontrol method of proposition of the embodiment of the present invention, movement are whole
End and computer readable storage medium are logical by using ultrasonic wave applied to the mobile terminal with Processing with Neural Network module
It crosses to approach and the detection far from movement determines the whether bright screen of mobile terminal and the screen that goes out, specifically mobile terminal uses neural network
Model carries out forecast analysis classification to the described eigenvector of the preprocessed generation of the ultrasonic signal of acquisition, approached/remote
The state occurred from movement judges classification, judges that classification controls screen state according to the state, it may be assumed that when the state judges class
When not being judged as close to (CLOSE), execution is gone out screen movement；When the state judges that classification is judged as far from (AWAY), execute
Bright screen movement；When the state judges that classification is judged as state constant (NORMAL), keep screen state constant；Mind of the invention
Have deep learning function through network model, there is powerful Nonlinear Modeling ability, can handle complicated scene change；Make
Classified with neural network model to feature vector, the discrimination and accuracy rate of ultrasonic distance measurement can be greatlyd improve, made
Realize that the automatic bright screen of mobile terminal screen, go out screen, improves user experience when user's making and receiving calls.
Detailed description of the invention
A kind of hardware structural diagram of Fig. 1 mobile terminal of each embodiment to realize the present invention；
Fig. 2 is a kind of communications network system architecture diagram provided in an embodiment of the present invention；
Fig. 3 is the flow diagram for the method that a kind of mobile terminal screen provided in an embodiment of the present invention automatically controls；
Fig. 4 is the structural schematic diagram for the device that a kind of mobile terminal screen provided in an embodiment of the present invention automatically controls；
Fig. 5 is the flow diagram for the method that a kind of mobile terminal screen provided in an embodiment of the present invention automatically controls；
Fig. 6 is the structural schematic diagram for the device that a kind of mobile terminal screen provided in an embodiment of the present invention automatically controls；
Fig. 7 is a kind of structural schematic diagram of mobile terminal provided in an embodiment of the present invention.
The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.
Specific embodiment
In order to be clearer and more clear technical problems, technical solutions and advantages to be solved, tie below
Drawings and examples are closed, the present invention will be described in further detail.It should be appreciated that specific embodiment described herein is only
To explain the present invention, it is not intended to limit the present invention.
In subsequent description, it is only using the suffix for indicating such as " module ", " component " or " unit " of element
Be conducive to explanation of the invention, itself there is no a specific meaning.Therefore, " module ", " component " or " unit " can mix
Ground uses.
It should be noted that description and claims of the invention are received and the term " first " in above-mentioned attached drawing, " the
Two " etc. be to be used to distinguish similar objects, without being used to describe a particular order or precedence order.
Terminal can be implemented in a variety of manners.For example, terminal described in the present invention may include such as mobile phone, plate
Computer, laptop, palm PC, personal digital assistant (Personal Digital Assistant, PDA), portable
Media player (Portable Media Player, PMP), navigation device, wearable device, Intelligent bracelet, pedometer etc. move
The fixed terminals such as dynamic terminal, and number TV, desktop computer.
It will be illustrated by taking mobile terminal as an example in subsequent descriptions, it will be appreciated by those skilled in the art that in addition to special
Except element for moving purpose, the construction of embodiment according to the present invention can also apply to the terminal of fixed type.
Referring to Fig. 1, a kind of hardware structural diagram of its mobile terminal of each embodiment to realize the present invention, the shifting
Dynamic terminal 100 may include: RF (Radio Frequency, radio frequency) unit 101, WiFi module 102, audio output unit
103, A/V (audio/video) input unit 104, sensor 105, display unit 106, user input unit 107, interface unit
108, the components such as memory 109, processor 110 and power supply 111.It will be understood by those skilled in the art that shown in Fig. 1
Mobile terminal structure does not constitute the restriction to mobile terminal, and mobile terminal may include components more more or fewer than diagram,
Perhaps certain components or different component layouts are combined.
It is specifically introduced below with reference to all parts of the Fig. 1 to mobile terminal:
Radio frequency unit 101 can be used for receiving and sending messages or communication process in, signal sends and receivees, specifically, by base station
Downlink information receive after, to processor 110 handle；In addition, the data of uplink are sent to base station.In general, radio frequency unit 101
Including but not limited to antenna, at least one amplifier, transceiver, coupler, low-noise amplifier, duplexer etc..In addition, penetrating
Frequency unit 101 can also be communicated with network and other equipment by wireless communication.Any communication can be used in above-mentioned wireless communication
Standard or agreement, including but not limited to GSM (Global System of Mobile communication, global system for mobile telecommunications
System), GPRS (General Packet Radio Service, general packet radio service), CDMA2000 (Code
Division Multiple Access 2000, CDMA 2000), WCDMA (Wideband Code Division
Multiple Access, wideband code division multiple access), TD-SCDMA (Time Division-Synchronous Code
Division Multiple Access, TD SDMA), FDD-LTE (Frequency Division
Duplexing-Long Term Evolution, frequency division duplex long term evolution) and TDD-LTE (Time Division
Duplexing-Long Term Evolution, time division duplex long term evolution) etc..
WiFi belongs to short range wireless transmission technology, and mobile terminal can help user to receive and dispatch electricity by WiFi module 102
Sub- mail, browsing webpage and access streaming video etc., it provides wireless broadband internet access for user.Although Fig. 1 shows
Go out WiFi module 102, but it is understood that, and it is not belonging to must be configured into for mobile terminal, it completely can be according to need
It to omit within the scope of not changing the essence of the invention.
Audio output unit 103 can be in call signal reception pattern, call mode, record mould in mobile terminal 100
When under the isotypes such as formula, speech recognition mode, broadcast reception mode, by radio frequency unit 101 or WiFi module 102 it is received or
The audio data stored in memory 109 is converted into audio signal and exports to be sound.Moreover, audio output unit 103
Audio output relevant to the specific function that mobile terminal 100 executes can also be provided (for example, call signal receives sound, disappears
Breath receives sound etc.).Audio output unit 103 may include loudspeaker, buzzer etc..
A/V input unit 104 is for receiving audio or video signal.A/V input unit 104 may include graphics processor
(Graphics Processing Unit, GPU) 1041 and microphone 1042, graphics processor 1041 is in video acquisition mode
Or the image data of the static images or video obtained in image capture mode by image capture apparatus (such as camera) carries out
Reason.Treated, and picture frame may be displayed on display unit 106.Through graphics processor 1041, treated that picture frame can be deposited
Storage is sent in memory 109 (or other storage mediums) or via radio frequency unit 101 or WiFi module 102.Mike
Wind 1042 can connect in telephone calling model, logging mode, speech recognition mode etc. operational mode via microphone 1042
Quiet down sound (audio data), and can be audio data by such acoustic processing.Audio that treated (voice) data can
To be converted to the format output that can be sent to mobile communication base station via radio frequency unit 101 in the case where telephone calling model.
Microphone 1042 can be implemented various types of noises elimination (or inhibition) algorithms and send and receive sound to eliminate (or inhibition)
The noise generated during frequency signal or interference.
Mobile terminal 100 further includes at least one sensor 105, such as optical sensor, motion sensor and other biographies
Sensor.Specifically, optical sensor includes ambient light sensor and proximity sensor, wherein ambient light sensor can be according to environment
The light and shade of light adjusts the brightness of display panel 1061, and proximity sensor can close when mobile terminal 100 is moved in one's ear
Display panel 1061 and/or backlight.As a kind of motion sensor, accelerometer sensor can detect in all directions (general
For three axis) size of acceleration, it can detect that size and the direction of gravity when static, can be used to identify the application of mobile phone posture
(such as horizontal/vertical screen switching, dependent game, magnetometer pose calibrating), Vibration identification correlation function (such as pedometer, percussion) etc.；
The fingerprint sensor that can also configure as mobile phone, pressure sensor, iris sensor, molecule sensor, gyroscope, barometer,
The other sensors such as hygrometer, thermometer, infrared sensor, details are not described herein.
Display unit 106 is for showing information input by user or being supplied to the information of user.Display unit 106 can wrap
Display panel 1061 is included, liquid crystal display (Liquid Crystal Display, LCD), Organic Light Emitting Diode can be used
Forms such as (Organic Light-Emitting Diode, OLED) configure display panel 1061.
User input unit 107 can be used for receiving the number or character information of input, and generate the use with mobile terminal
Family setting and the related key signals input of function control.Specifically, user input unit 107 may include touch panel 1071 with
And other input equipments 1072.Touch panel 1071, also referred to as touch screen collect the touch operation of user on it or nearby
(for example user uses any suitable objects or attachment such as finger, stylus on touch panel 1071 or in touch panel 1071
Neighbouring operation), and corresponding attachment device is driven according to preset formula.Touch panel 1071 may include touch detection
Two parts of device and touch controller.Wherein, the touch orientation of touch detecting apparatus detection user, and detect touch operation band
The signal come, transmits a signal to touch controller；Touch controller receives touch information from touch detecting apparatus, and by it
It is converted into contact coordinate, then gives processor 110, and order that processor 110 is sent can be received and executed.In addition, can
To realize touch panel 1071 using multiple types such as resistance-type, condenser type, infrared ray and surface acoustic waves.In addition to touch panel
1071, user input unit 107 can also include other input equipments 1072.Specifically, other input equipments 1072 can wrap
It includes but is not limited in physical keyboard, function key (such as volume control button, switch key etc.), trace ball, mouse, operating stick etc.
It is one or more, specifically herein without limitation.
Further, touch panel 1071 can cover display panel 1061, when touch panel 1071 detect on it or
After neighbouring touch operation, processor 110 is sent to determine the type of touch event, is followed by subsequent processing device 110 according to touch thing
The type of part provides corresponding visual output on display panel 1061.Although in Fig. 1, touch panel 1071 and display panel
1061 be the function that outputs and inputs of realizing mobile terminal as two independent components, but in certain embodiments, it can
The function that outputs and inputs of mobile terminal is realized so that touch panel 1071 and display panel 1061 is integrated, is not done herein specifically
It limits.
Interface unit 108 be used as at least one external device (ED) connect with mobile terminal 100 can by interface.For example,
External device (ED) may include wired or wireless headphone port, external power supply (or battery charger) port, wired or nothing
Line data port, memory card port, the port for connecting the device with identification module, audio input/output (I/O) end
Mouth, video i/o port, ear port etc..Interface unit 108 can be used for receiving the input from external device (ED) (for example, number
It is believed that breath, electric power etc.) and the input received is transferred to one or more elements in mobile terminal 100 or can be with
For transmitting data between mobile terminal 100 and external device (ED).
Memory 109 can be used for storing software program and various data.Memory 109 can mainly include storing program area
The storage data area and, wherein storing program area can (such as the sound of application program needed for storage program area, at least one function
Sound playing function, image player function etc.) etc.；Storage data area can store according to mobile phone use created data (such as
Audio data, phone directory etc.) etc..In addition, memory 109 may include high-speed random access memory, it can also include non-easy
The property lost memory, a for example, at least disk memory, flush memory device or other volatile solid-state parts.
Processor 110 is the control centre of mobile terminal, utilizes each of various interfaces and the entire mobile terminal of connection
A part by running or execute the software program and/or module that are stored in memory 109, and calls and is stored in storage
Data in device 109 execute the various functions and processing data of mobile terminal, to carry out integral monitoring to mobile terminal.Place
Managing device 110 may include one or more processing units；Preferably, processor 110 can integrate application processor and modulatedemodulate is mediated
Manage device, wherein the main processing operation system of application processor, user interface and application program etc., modem processor is main
Processing wireless communication.It is understood that above-mentioned modem processor can not also be integrated into processor 110.
Mobile terminal 100 can also include the power supply 111 (such as battery) powered to all parts, it is preferred that power supply 111
Can be logically contiguous by power-supply management system and processor 110, to realize management charging by power-supply management system, put
The functions such as electricity and power managed.
Although Fig. 1 is not shown, mobile terminal 100 can also be including bluetooth module etc., and details are not described herein.
Embodiment to facilitate the understanding of the present invention, the communications network system that mobile terminal of the invention is based below into
Row description.
Referring to Fig. 2, Fig. 2 is a kind of communications network system architecture diagram provided in an embodiment of the present invention, the communication network system
System is the LTE system of universal mobile communications technology, which includes UE (User Equipment, the use of successively communication connection
Family equipment) (the land Evolved UMTS Terrestrial Radio Access Network, evolved UMTS 201, E-UTRAN
Ground wireless access network) 202, EPC (Evolved Packet Core, evolved packet-based core networks) 203 and operator IP operation
204。
Specifically, UE201 can be above-mentioned terminal 100, and details are not described herein again.
E-UTRAN202 includes eNodeB2021 and other eNodeB2022 etc..Wherein, eNodeB2021 can be by returning
Journey (backhaul) (such as X2 interface) is connect with other eNodeB2022, and eNodeB2021 is connected to EPC203,
ENodeB2021 can provide the access of UE201 to EPC203.
EPC203 may include MME (Mobility Management Entity, mobility management entity) 2031, HSS
(Home Subscriber Server, home subscriber server) 2032, other MME2033, SGW (Serving Gate Way,
Gateway) 2034, PGW (PDN Gate Way, grouped data network gateway) 2035 and PCRF (Policy and
Charging Rules Function, policy and rate functional entity) 2036 etc..Wherein, MME2031 be processing UE201 and
The control node of signaling, provides carrying and connection management between EPC203.HSS2032 is all to manage for providing some registers
Such as the function of home location register (not shown) etc, and preserves some related service features, data rates etc. and use
The dedicated information in family.All customer data can be sent by SGW2034, and PGW2035 can provide the IP of UE 201
Address distribution and other functions, PCRF2036 are strategy and the charging control strategic decision-making of business data flow and IP bearing resource
Point, it selects and provides available strategy and charging control decision with charge execution function unit (not shown) for strategy.
IP operation 204 may include internet, Intranet, IMS (IP Multimedia Subsystem, IP multimedia
System) or other IP operations etc..
Although above-mentioned be described by taking LTE system as an example, those skilled in the art should know the present invention is not only
Suitable for LTE system, be readily applicable to other wireless communication systems, such as GSM, CDMA2000, WCDMA, TD-SCDMA with
And the following new network system etc., herein without limitation.
Based on above-mentioned mobile terminal hardware configuration and communications network system, each embodiment of the method for the present invention is proposed.
Please refer to Fig. 3.The embodiment of the present invention provides a kind of method that mobile terminal screen automatically controls, and is applied to have mind
Mobile terminal through network process module controls screen bright screen and the screen that goes out automatically using ultrasonic wave, comprising:
Step S1, ultrasonic signal is acquired；
Step S2, the collected ultrasonic signal is pre-processed, generates feature vector；
Step S3, status categories are obtained using the Processing with Neural Network module forecast analysis described eigenvector；
Step S4, screen state is controlled according to the status categories.
Further, in step S1, the acquisition ultrasonic signal is conducted through the direct sound wave come including structural vibration and leads to
Cross the reflected reflected sound in head.
Further, described that the collected ultrasonic signal is pre-processed in step S2, generate feature to
Amount, comprising: the collected ultrasonic signal is carried out to include at least one of framing, spectrum analysis, characteristic vector pickup
Pretreatment, generate feature vector；Wherein, described eigenvector reaction is shelter in approach and far from mobile terminal front
The changing rule of the collected ultrasonic wave of Shi Suoshu ultrasonic acquisition module.
Further, described to be obtained using the Processing with Neural Network module forecast analysis described eigenvector in step S3
To status categories, comprising:
Step S31, the described mobile terminal uses the Processing with Neural Network module forecast analysis described eigenvector, detection
Approach movement and the generation far from movement；Include:
The mobile terminal is formed using the Processing with Neural Network module by extracting to be extracted by raw ultrasound signals
Described eigenvector in a period of time course feature, such as the transient state characteristic of a bit of time will be in this section of time history
The characteristic value constitutive characteristic vector that the feature calculation of different periods obtains, analytic learning form the variation rule of this section of time history
Rule, obtains the network model weight of the Processing with Neural Network module, obtains the neural network of the Processing with Neural Network module
Model.When carry out close to/far from judge when, the neural network model of the Processing with Neural Network module is analyzed the ultrasonic wave and is believed
The described eigenvector that number preprocessing module generates, detects whether relevant action, the state of obtaining judges classification, that is, utilizes
Neural network model classifies to described eigenvector, and the state of obtaining judges classification.
Step S32, the described mobile terminal is acted according to approach using the Processing with Neural Network module and far from movement
The testing result of generation, obtains status categories, comprising:
The mobile terminal uses prediction after the Processing with Neural Network module analysis described eigenvector to have approach movement
When generation, judge status categories for close to (CLOSE)；
The mobile terminal uses prediction after the Processing with Neural Network module analysis described eigenvector to have separate movement
When generation, judge status categories for far from (AWAY)；
The mobile terminal is predicted to move without approach after using the Processing with Neural Network module analysis described eigenvector
When making or occurring far from movement, judge that status categories are constant (NORMAL) for state.
It is further, described to control screen state according to the status categories in step S4, comprising:
When the status categories are close, screen movement of going out is executed；When the status categories are separate, bright screen movement is executed；
When the status categories are that state is constant, keep screen state constant.
The method that a kind of mobile terminal screen provided in an embodiment of the present invention automatically controls automatically controls screen bright screen automatically
Shield with going out, applied to the mobile terminal with Processing with Neural Network module.The embodiment of the present invention is by approach and far from dynamic
The detection of work determines the whether bright screen of mobile terminal and the screen that goes out, rather than the absolute distance by measuring shelter carry out bright screen with
Go out what screen judged.Specifically mobile terminal is using neural network model to described in the preprocessed generation of the ultrasonic signal of acquisition
Feature vector carries out forecast analysis classification, and the state for being approached/being occurred far from movement judges classification, is judged according to the state
Classification controls screen state, it may be assumed that when the state judge that classification is judged as close to (CLOSE), the execution screen that goes out is acted；When described
When state judges that classification is judged as far from (AWAY), bright screen movement is executed；When the state judges that classification is judged as that state is constant
(NORMAL) when, keep screen state constant.The embodiment of the present invention uses deep learning principle, and mobile terminal uses neural network
Model classifies to feature vector, can greatly improve the discrimination and accuracy rate of ultrasonic distance measurement, take user
Realize that the automatic bright screen of mobile terminal screen, go out screen, improves user experience when phone.
Please refer to Fig. 4.The embodiment of the invention provides the devices that a kind of mobile terminal screen automatically controls, using ultrasonic wave
It bright screen and goes out screen automatically to control screen, applied to the mobile terminal with Processing with Neural Network module, comprising: ultrasonic acquisition
Module 10, ultrasonic signal preprocessing module 20, Processing with Neural Network module 30, in which:
The ultrasonic acquisition module 10, for acquiring ultrasonic signal.
The ultrasonic signal preprocessing module 20, it is raw for being pre-processed to the collected ultrasonic signal
At feature vector；Wherein, the pretreatment includes at least following one kind: spectrum analysis, framing, characteristic vector pickup.
The Processing with Neural Network mould 30 carries out obtaining status categories, Yi Jigen for forecast analysis described eigenvector
Screen state is controlled according to the status categories.
Further, the ultrasonic acquisition module 10, is specifically used for: acquisition ultrasonic signal, including structural vibration pass
The direct sound wave led and pass through the reflected reflected sound in head.
Preferably, the ultrasonic acquisition module 10 is ultrasonic microphone, and the ultrasonic microphone is super for acquiring
Acoustic signals.
Further, the ultrasonic signal preprocessing module 20, is specifically used for: to the collected ultrasonic signal
It carries out including at least one pretreatment such as framing, spectrum analysis, characteristic vector pickup, generates feature vector.Wherein, the spy
Levying to quantitative response is shelter collected ultrasound of ultrasonic acquisition module in approach and separate mobile terminal front
The changing rule of wave.
Further, the Processing with Neural Network module 30, is specifically used for:
The 30 forecast analysis described eigenvector of Processing with Neural Network module, obtains status categories, wherein the state
Classification includes: close to (CLOSE), and separate (AWAY), state are constant (NORMAL)；
The Processing with Neural Network module 30 controls screen state according to the status categories, comprising: the status categories
When to approach, screen movement of going out is executed；When the status categories are separate, bright screen movement is executed；The status categories be state not
When change, keep screen state constant.
Further, the 30 forecast analysis described eigenvector of Processing with Neural Network module, obtains status categories, packet
It includes:
The 30 forecast analysis described eigenvector of Processing with Neural Network module, the movement of detection approach and the hair far from movement
It is raw, comprising: the Processing with Neural Network module 30 is extracted the described eigenvector formed by raw ultrasound signals by extracting
The feature of middle a period of time course, such as the transient state characteristic of a bit of time, by the feature of different periods in this section of time history
The characteristic value constitutive characteristic vector being calculated, analytic learning form the changing rule of this section of time history, obtain the nerve
The network model weight of network process module 30 obtains the neural network model of the Processing with Neural Network module 30.Work as progress
Close/far from when judging, the neural network model of the Processing with Neural Network module 30 analyzes the ultrasonic signal pretreatment
The described eigenvector that module generates, detects whether relevant action, and the state of obtaining judges classification, that is, utilizes neural network
Model classifies to described eigenvector, and the state of obtaining judges classification.
And the testing result according to approach movement and the generation far from movement, obtain status categories, comprising:
When prediction has approach movement to occur after the analysis of Processing with Neural Network module 30 described eigenvector, state is judged
Classification is close to (CLOSE)；
When there is far from movement generation prediction after the analysis of Processing with Neural Network module 30 described eigenvector, state is judged
Classification is far from (AWAY)；
Prediction does not have approach to act or far from movement hair after the Processing with Neural Network module 30 analyzes described eigenvector
When raw, judge that status categories are constant (NORMAL) for state.
The device that a kind of mobile terminal screen provided in an embodiment of the present invention automatically controls automatically controls screen bright screen automatically
Shield with going out, applied to the mobile terminal with Processing with Neural Network module.The embodiment of the present invention is by approach and far from dynamic
The detection of work determines the whether bright screen of mobile terminal and the screen that goes out, rather than the absolute distance by measuring shelter carry out bright screen with
Go out what screen judged.Specifically mobile terminal uses the ultrasonic signal that acquires to the ultrasonic acquisition module of neural network model
The described eigenvector generated through ultrasonic signal preprocessing module pretreatment carries out forecast analysis classification, approached/
The state occurred far from movement judges classification, judges that classification controls screen state according to the state, it may be assumed that when the state judges
When classification is judged as close to (CLOSE), execution is gone out screen movement；When the state judges that classification is judged as far from (AWAY), hold
The bright screen movement of row；When the state judges that classification is judged as state constant (NORMAL), keep screen state constant.The present invention
Embodiment uses deep learning principle, is classified using neural network model to feature vector, can greatly improve ultrasound
The discrimination and accuracy rate of wave ranging make user realize that the automatic bright screen of mobile terminal screen, go out screen in making and receiving calls, improve
User experience.
It should be noted that above-mentioned apparatus embodiment and embodiment of the method belong to same design, specific implementation process is detailed
See embodiment of the method, and the technical characteristic in embodiment of the method is corresponding applicable in described device embodiment, it is no longer superfluous here
It states.
This programme is classified using artificial nerve network model to feature vector value using deep learning principle, can
To greatly improve discrimination.Particularly input audio initial data carries out model training, then obtains network model power
Value obtains the final Ultrasound Model that we need.When carry out close to/far from judge when, acquisition feature vector, then use nerve net
Network model is classified, and measured result can greatly improve accuracy rate.
Technical solution of the present invention is described in further detail with reference to embodiments.
Please refer to Fig. 5.
A kind of method that mobile terminal screen automatically controls is controlled screen bright screen and the screen that goes out automatically using ultrasonic wave, answered
For the mobile terminal with Processing with Neural Network module, which comprises
Step S401, ultrasonic signal is acquired, be conducted through the direct sound wave come including structural vibration and is reflected back by head
The reflected sound come.
Step S402, the collected ultrasonic signal is pre-processed, generates feature vector；Wherein, described pre-
Processing includes at least following at least one: framing, spectrum analysis, characteristic vector pickup.Described eigenvector reaction is to block
The changing rule of object collected ultrasonic wave of ultrasonic acquisition module in approach and separate mobile terminal front.
Step S403, using the Processing with Neural Network module forecast analysis described eigenvector, detect approach movement and
Generation far from movement；Include:
The mobile terminal is formed using the Processing with Neural Network module by extracting to be extracted by raw ultrasound signals
Described eigenvector in a period of time course feature, such as the transient state characteristic of a bit of time will be in this section of time history
The characteristic value constitutive characteristic vector that the feature calculation of different periods obtains, analytic learning form the variation rule of this section of time history
Rule, obtains the network model weight of the Processing with Neural Network module, obtains the neural network of the Processing with Neural Network module
Model.When carry out close to/far from judge when, the neural network model of the Processing with Neural Network module is analyzed the ultrasonic wave and is believed
The described eigenvector that number preprocessing module generates, detects whether relevant action, the state of obtaining judges classification, that is, utilizes
Neural network model classifies to described eigenvector, and the state of obtaining judges classification.
Step S404, the described mobile terminal is acted according to approach using the Processing with Neural Network module and far from movement
The testing result of generation, obtains status categories, comprising:
The mobile terminal uses prediction after the Processing with Neural Network module analysis described eigenvector to have approach movement
When generation, judge status categories for close to (CLOSE)；
The mobile terminal uses prediction after the Processing with Neural Network module analysis described eigenvector to have separate movement
When generation, judge status categories for far from (AWAY)；
The mobile terminal is predicted to move without approach after using the Processing with Neural Network module analysis described eigenvector
When making or occurring far from movement, judge that status categories are constant (NORMAL) for state.
Step S405, screen state is controlled according to the status categories, comprising:
When the status categories are close, screen movement of going out is executed；When the status categories are separate, bright screen movement is executed；
When the status categories are that state is constant, keep screen state constant.
Please refer to Fig. 6.
In the present embodiment, the ultrasonic acquisition module is illustrated by taking ultrasonic microphone as an example.
A kind of device that mobile terminal screen automatically controls is controlled screen bright screen and the screen that goes out automatically using ultrasonic wave, answered
For the mobile terminal with Processing with Neural Network module, comprising: ultrasonic microphone 10, ultrasonic signal preprocessing module
20, Processing with Neural Network module 30, in which:
The ultrasonic microphone 10, for acquiring ultrasonic signal, including structural vibration be conducted through come direct sound wave and
Pass through the reflected reflected sound in head.
The ultrasonic signal preprocessing module 20, it is raw for being pre-processed to the collected ultrasonic signal
At feature vector；Wherein, the pretreatment includes at least following one kind: spectrum analysis, framing, characteristic vector pickup.Wherein, institute
State feature vector reaction is that shelter ultrasonic microphone in approach and separate mobile terminal front is collected super
The changing rule of sound wave.
The Processing with Neural Network module 30 carries out obtaining status categories for forecast analysis described eigenvector, and
Screen state is controlled according to the status categories.It is specifically used for:
The 30 forecast analysis described eigenvector of Processing with Neural Network module, obtains status categories, wherein the state
Classification includes: close to (CLOSE), and separate (AWAY), state are constant (NORMAL).Include:
The 30 forecast analysis described eigenvector of Processing with Neural Network module, the movement of detection approach and the hair far from movement
It is raw, comprising: the Processing with Neural Network module 30 is extracted the described eigenvector formed by raw ultrasound signals by extracting
The feature of middle a period of time course, such as the transient state characteristic of a bit of time, by the feature of different periods in this section of time history
The characteristic value constitutive characteristic vector being calculated, analytic learning form the changing rule of this section of time history, obtain the nerve
The network model weight of network process module 30 obtains the neural network model of the Processing with Neural Network module 30.Work as progress
Close/far from when judging, the neural network model of the Processing with Neural Network module 30 analyzes the ultrasonic signal pretreatment
The described eigenvector that module generates, detects whether relevant action, and the state of obtaining judges classification, that is, utilizes neural network
Model classifies to described eigenvector, and the state of obtaining judges classification.
And the testing result according to approach movement and the generation far from movement, obtain status categories, comprising:
When prediction has approach movement to occur after the analysis of Processing with Neural Network module 30 described eigenvector, state is judged
Classification is close to (CLOSE)；
When there is far from movement generation prediction after the analysis of Processing with Neural Network module 30 described eigenvector, state is judged
Classification is far from (AWAY)；
Prediction does not have approach to act or far from movement hair after the Processing with Neural Network module 30 analyzes described eigenvector
When raw, judge that status categories are constant (NORMAL) for state.
The Processing with Neural Network module 30 controls screen state according to the status categories, comprising: the status categories
When to approach, screen movement of going out is executed；When the status categories are separate, bright screen movement is executed；The status categories be state not
When change, keep screen state constant.
In addition, the embodiment of the present invention also provides a kind of mobile terminal, as shown in fig. 7, the mobile terminal 900 includes: to deposit
Reservoir 902, processor 901 and it is stored in one for can running in the memory 902 and on the processor 901 or more
A computer program, the memory 902 and the processor 901 are coupled by bus system 903, it is one or
To realize a kind of mobile terminal screen provided in an embodiment of the present invention when the multiple computer programs of person are executed by the processor 901
The following steps of the method for automatic control:
Step S1, ultrasonic signal is acquired；
Step S2, the collected ultrasonic signal is pre-processed, generates feature vector；
Step S3, status categories are obtained using the Processing with Neural Network module forecast analysis described eigenvector；
Step S4, screen state is controlled according to the status categories.
Further, in step S1, the acquisition ultrasonic signal is conducted through the direct sound wave come including structural vibration and leads to
Cross the reflected reflected sound in head.
Further, described that the collected ultrasonic signal is pre-processed in step S2, generate feature to
Amount, comprising: the collected ultrasonic signal is carried out to include at least one of framing, spectrum analysis, characteristic vector pickup
Pretreatment, generate feature vector；Wherein, described eigenvector reaction is shelter in approach and far from mobile terminal front
The changing rule of the collected ultrasonic wave of Shi Suoshu ultrasonic acquisition module.
Further, described to be obtained using the Processing with Neural Network module forecast analysis described eigenvector in step S3
To status categories, comprising:
Step S31, the described mobile terminal uses the Processing with Neural Network module forecast analysis described eigenvector, detection
Approach movement and the generation far from movement；Include:
The mobile terminal is formed using the Processing with Neural Network module by extracting to be extracted by raw ultrasound signals
Described eigenvector in a period of time course feature, such as the transient state characteristic of a bit of time will be in this section of time history
The characteristic value constitutive characteristic vector that the feature calculation of different periods obtains, analytic learning form the variation rule of this section of time history
Rule, obtains the network model weight of the Processing with Neural Network module, obtains the neural network of the Processing with Neural Network module
Model.When carry out close to/far from judge when, the neural network model of the Processing with Neural Network module is analyzed the ultrasonic wave and is believed
The described eigenvector that number preprocessing module generates, detects whether relevant action, the state of obtaining judges classification, that is, utilizes
Neural network model classifies to described eigenvector, and the state of obtaining judges classification.
Step S32, the described mobile terminal is acted according to approach using the Processing with Neural Network module and far from movement
The testing result of generation, obtains status categories, comprising:
The mobile terminal uses prediction after the Processing with Neural Network module analysis described eigenvector to have approach movement
When generation, judge status categories for close to (CLOSE)；
The mobile terminal uses prediction after the Processing with Neural Network module analysis described eigenvector to have separate movement
When generation, judge status categories for far from (AWAY)；
The mobile terminal is predicted to move without approach after using the Processing with Neural Network module analysis described eigenvector
When making or occurring far from movement, judge that status categories are constant (NORMAL) for state.
It is further, described to control screen state according to the status categories in step S4, comprising:
When the status categories are close, screen movement of going out is executed；When the status categories are separate, bright screen movement is executed；
When the status categories are that state is constant, keep screen state constant.
The method that the embodiments of the present invention disclose can be applied in the processor 901, or by the processor
901 realize.The processor 901 may be a kind of IC chip, have signal handling capacity.During realization, on
Each step for stating method can be complete by the integrated logic circuit of the hardware in the processor 901 or the instruction of software form
At.The processor 901 can be general processor, DSP or other programmable logic device, discrete gate or transistor
Logical device, discrete hardware components etc..The processor 901 may be implemented or execute disclosed each in the embodiment of the present invention
Method, step and logic diagram.General processor can be microprocessor or any conventional processor etc..In conjunction with the present invention
The step of method disclosed in embodiment, can be embodied directly in hardware decoding processor and execute completion, or be handled with decoding
Hardware and software module combination in device execute completion.Software module can be located in storage medium, which, which is located at, deposits
The step of reservoir 902, the processor 901 reads the information in memory 902, completes preceding method in conjunction with its hardware.
It is appreciated that the memory 902 of the embodiment of the present invention can be volatile memory or nonvolatile memory,
It also may include both volatile and non-volatile memories.Wherein, nonvolatile memory can be read-only memory (ROM,
Read-Only Memory), it is programmable read only memory (PROM, Programmable Read-Only Memory), erasable
Programmable read only memory (EPROM, Erasable Read-Only Memory), electricallyerasable ROM (EEROM) (EEPROM,
Electrically Erasable Programmable Read-Only Memory), magnetic RAM (FRAM,
Ferromagnetic Random Access Memory), flash memory (Flash Memory) or other memory technologies, CD only
Read memory (CD-ROM, Compact Disk Read-Only Memory), digital versatile disc (DVD, Digital Video
) or other optical disc storages, magnetic holder, tape, disk storage or other magnetic memory apparatus Disk；Volatile memory can be at random
It accesses memory (RAM, Random Access Memory), by exemplary but be not restricted explanation, the RAM of many forms
It can use, such as static random access memory (SRAM, Static Random Access Memory), static random-access are deposited
Reservoir (SSRAM, Synchronous Static Random Access Memory), dynamic random access memory (DRAM,
Dynamic Random Access Memory), Synchronous Dynamic Random Access Memory (SDRAM, Synchronous
Dynamic Random Access Memory), double data speed synchronous dynamic RAM (DDRSDRAM,
Double Data Rate Synchronous Dynamic Random Access Memory), enhanced synchronous dynamic random
Access memory (ESDRAM, Enhanced Synchronous Dynamic Random Access Memory), synchronized links
Dynamic random access memory (SLDRAM, SyncLink Dynamic Random Access Memory), direct rambus
Random access memory (DRRAM, Direct Rambus Random Access Memory).Description of the embodiment of the present invention is deposited
Reservoir is intended to include but is not limited to the memory of these and any other suitable type.
It should be noted that above-mentioned mobile terminal embodiment and embodiment of the method belong to same design, implemented
Journey is detailed in embodiment of the method, and the technical characteristic in embodiment of the method is corresponding applicable in the mobile terminal embodiment, this
In repeat no more.
In addition, in the exemplary embodiment, the embodiment of the present invention also provides a kind of computer readable storage medium, specially
Computer readable storage medium stores in the computer storage medium for example including the memory 902 for storing computer program
One or more program for the method for thering is mobile terminal screen to automatically control, the method that the mobile terminal screen automatically controls
One or more program by processor 901 execute when with realize a kind of mobile terminal screen provided in an embodiment of the present invention from
The following steps of the method for dynamic control:
Step S1, ultrasonic signal is acquired；
Step S2, the collected ultrasonic signal is pre-processed, generates feature vector；
Step S3, status categories are obtained using the Processing with Neural Network module forecast analysis described eigenvector；
Step S4, screen state is controlled according to the status categories.
Further, in step S1, the acquisition ultrasonic signal is conducted through the direct sound wave come including structural vibration and leads to
Cross the reflected reflected sound in head.
Further, described that the collected ultrasonic signal is pre-processed in step S2, generate feature to
Amount, comprising: the collected ultrasonic signal is carried out to include at least one of framing, spectrum analysis, characteristic vector pickup
Pretreatment, generate feature vector；Wherein, described eigenvector reaction is shelter in approach and far from mobile terminal front
The changing rule of the collected ultrasonic wave of Shi Suoshu ultrasonic acquisition module.
Further, described to be obtained using the Processing with Neural Network module forecast analysis described eigenvector in step S3
To status categories, comprising:
Step S31, the described mobile terminal uses the Processing with Neural Network module forecast analysis described eigenvector, detection
Approach movement and the generation far from movement；Include:
The mobile terminal is formed using the Processing with Neural Network module by extracting to be extracted by raw ultrasound signals
Described eigenvector in a period of time course feature, such as the transient state characteristic of a bit of time will be in this section of time history
The characteristic value constitutive characteristic vector that the feature calculation of different periods obtains, analytic learning form the variation rule of this section of time history
Rule, obtains the network model weight of the Processing with Neural Network module, obtains the neural network of the Processing with Neural Network module
Model.When carry out close to/far from judge when, the neural network model of the Processing with Neural Network module is analyzed the ultrasonic wave and is believed
The described eigenvector that number preprocessing module generates, detects whether relevant action, the state of obtaining judges classification, that is, utilizes
Neural network model classifies to described eigenvector, and the state of obtaining judges classification.
Step S32, the described mobile terminal is acted according to approach using the Processing with Neural Network module and far from movement
The testing result of generation, obtains status categories, comprising:
The mobile terminal uses prediction after the Processing with Neural Network module analysis described eigenvector to have approach movement
When generation, judge status categories for close to (CLOSE)；
The mobile terminal uses prediction after the Processing with Neural Network module analysis described eigenvector to have separate movement
When generation, judge status categories for far from (AWAY)；
The mobile terminal is predicted to move without approach after using the Processing with Neural Network module analysis described eigenvector
When making or occurring far from movement, judge that status categories are constant (NORMAL) for state.
It is further, described to control screen state according to the status categories in step S4, comprising:
When the status categories are close, screen movement of going out is executed；When the status categories are separate, bright screen movement is executed；
When the status categories are that state is constant, keep screen state constant.
It should be noted that the method program that the mobile terminal screen on above-mentioned computer readable storage medium automatically controls
Embodiment and embodiment of the method belong to same design, and specific implementation process is detailed in embodiment of the method, and in embodiment of the method
Technical characteristic is corresponding in the embodiment of above-mentioned computer readable storage medium to be applicable in, and which is not described herein again.
It should be noted that, in this document, the terms "include", "comprise" or its any other variant are intended to non-row
His property includes, so that the process, method, article or the device that include a series of elements not only include those elements, and
And further include other elements that are not explicitly listed, or further include for this process, method, article or device institute it is intrinsic
Element.In the absence of more restrictions, the element limited by sentence " including one ... ", it is not excluded that including
There is also other identical elements in the process, method of the element, article or device.
The serial number of the above embodiments of the invention is only for description, does not represent the advantages or disadvantages of the embodiments.
Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment side
Method can be realized by means of software and necessary general hardware platform, naturally it is also possible to by hardware, but in many cases
The former is more preferably embodiment.Based on this understanding, technical solution of the present invention substantially in other words does the prior art
The part contributed out can be embodied in the form of software products, which is stored in a storage medium
In (such as ROM/RAM, magnetic disk, CD), including some instructions are used so that a terminal (can be mobile phone, computer, service
Device, air conditioner or network equipment etc.) execute method described in each embodiment of the present invention.
The embodiment of the present invention is described with above attached drawing, but the invention is not limited to above-mentioned specific
Embodiment, the above mentioned embodiment is only schematical, rather than restrictive, those skilled in the art
Under the inspiration of the present invention, without breaking away from the scope protected by the purposes and claims of the present invention, it can also make very much
Form, all of these belong to the protection of the present invention.
Claims (10)
1. a kind of method that mobile terminal screen automatically controls, applied to the mobile terminal with Processing with Neural Network module,
It is characterized in that, comprising:
Acquire ultrasonic signal；
The collected ultrasonic signal is pre-processed, feature vector is generated；
Status categories are obtained using the Processing with Neural Network module forecast analysis described eigenvector；
Screen state is controlled according to the status categories.
2. the method according to claim 1, wherein the acquisition ultrasonic signal, including structural vibration are conducted
The direct sound wave that comes over and pass through the reflected reflected sound in head.
3. the method according to claim 1, wherein described locate the collected ultrasonic signal in advance
Reason, comprising: following at least one pretreatment carried out to the collected ultrasonic signal: framing, spectrum analysis, feature to
Amount is extracted.
4. method according to claim 1 or 3, which is characterized in that described eigenvector reaction is that shelter is approaching
The changing rule of collected ultrasonic wave when with far from mobile terminal front.
5. the method according to claim 1, wherein described use the Processing with Neural Network module forecast analysis
Described eigenvector obtains status categories, comprising:
The mobile terminal uses the Processing with Neural Network module forecast analysis described eigenvector, detection approach movement and remote
Generation from movement；
The mobile terminal is acted using the Processing with Neural Network module according to approach and the detection knot of the generation far from movement
Fruit obtains status categories.
6. according to the method described in claim 5, it is characterized in that, the mobile terminal uses the Processing with Neural Network module
Forecast analysis described eigenvector, the movement of detection approach and the generation far from movement, comprising:
The mobile terminal extracted using the Processing with Neural Network module extracted from ultrasonic signal the feature that is formed to
The feature of a period of time course in amount, the characteristic value constitutive characteristic that the feature calculation of different periods in this section of time history is obtained
Vector, analytic learning form the changing rule of this section of time history, obtain the network model power of the Processing with Neural Network module
Value, obtains the neural network model of the Processing with Neural Network module；
The neural network model of the Processing with Neural Network module analyzes the described of the ultrasonic signal preprocessing module generation
Feature vector, the movement of detection approach and separate generation.
7. according to the method described in claim 5, it is characterized in that, the mobile terminal uses the Processing with Neural Network module
According to the testing result of approach movement and the generation far from movement, status categories are obtained, comprising:
The mobile terminal uses prediction after the Processing with Neural Network module analysis described eigenvector to have approach movement
When, judge that status categories are close；
The mobile terminal uses prediction after the Processing with Neural Network module analysis described eigenvector to have far from movement
When, judge status categories to be separate；
The mobile terminal use the Processing with Neural Network module analysis described eigenvector after prediction do not have approach act or
When occurring far from movement, judge that status categories are constant for state.
8. the method according to the description of claim 7 is characterized in that described control screen state, packet according to the status categories
It includes:
When the status categories are close, screen movement of going out is executed；
When the status categories are separate, bright screen movement is executed；
When the status categories are that state is constant, keep screen state constant.
9. a kind of mobile terminal characterized by comprising memory, processor and be stored on the memory and can be in institute
The computer program run on processor is stated, such as claim 1 to 8 is realized when the computer program is executed by the processor
Any one of described in mobile terminal screen automatically control method the step of.
10. a kind of computer readable storage medium, which is characterized in that be stored on the computer readable storage medium mobile whole
When the program of the program for the method for holding screen to automatically control, the method that the mobile terminal screen automatically controls is executed by processor
The step of realizing the method such as mobile terminal screen described in any item of the claim 1 to 8 automatic control.
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