Kozlova et al., 2018 - Google Patents
The use of neural networks for planning the behavior of complex systemsKozlova et al., 2018
- Document ID
- 1869857129838767935
- Author
- Kozlova L
- Belov A
- Kozlova O
- Publication year
- Publication venue
- 2018 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus)
External Links
Snippet
The use of neural networks for planning the behavior of complex systems Page 1 902 978-1-5386-4340-2/18/$31.00
©2018 IEEE The Use of Neural Networks for Planning the Behavior of Complex Systems
Liudmila P. Kozlova1, Alexsandr M. Belov2 Faculty of Industrial Automation and Electrical …
- 230000001537 neural 0 title abstract description 19
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/08—Learning methods
- G06N3/082—Learning methods modifying the architecture, e.g. adding or deleting nodes or connections, pruning
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/06—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
- G06N3/063—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
- G06N3/0635—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means using analogue means
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/04—Architectures, e.g. interconnection topology
- G06N3/0454—Architectures, e.g. interconnection topology using a combination of multiple neural nets
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/04—Architectures, e.g. interconnection topology
- G06N3/0472—Architectures, e.g. interconnection topology using probabilistic elements, e.g. p-rams, stochastic processors
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/10—Simulation on general purpose computers
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
- G05B13/027—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using neural networks only
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
- G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
- G06K9/6251—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on a criterion of topology preservation, e.g. multidimensional scaling, self-organising maps
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/004—Artificial life, i.e. computers simulating life
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/12—Computer systems based on biological models using genetic models
- G06N3/126—Genetic algorithms, i.e. information processing using digital simulations of the genetic system
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/04—Inference methods or devices
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/02—Knowledge representation
- G06N5/022—Knowledge engineering, knowledge acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N7/00—Computer systems based on specific mathematical models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Kukreja et al. | An introduction to artificial neural network | |
Werbos | Neural networks for control and system identification | |
Thakur et al. | Fundamentals of neural networks | |
Eluyode et al. | Comparative study of biological and artificial neural networks | |
US8874498B2 (en) | Unsupervised, supervised, and reinforced learning via spiking computation | |
Zhao et al. | Synchronization of coupled memristive competitive BAM neural networks with different time scales | |
Kozlova et al. | The use of neural networks for planning the behavior of complex systems | |
Kohli et al. | Basics of artificial neural network | |
Kamarthi et al. | Neural networks and their applications in component design data retrieval | |
Zilouchian | Fundamentals of neural networks | |
Chen | Neural networks in pattern recognition and their applications | |
Garczarczyk | Interval neural networks | |
Maliavko et al. | Towards development of self-learning and self-modification spiking neural network as model of brain | |
Reda | Deep learning an overview | |
Zins et al. | Reproducing Fear Conditioning of Rats with Unmanned Ground Vehicles and Neuromorphic Systems | |
Gruodis | Realizations of the Artificial Neural Network for Process Modeling. Overview of Current Implementations | |
Ali | Introduction to Neural Networks | |
Lechuga-Gutiérrez et al. | Quaternion spike neural networks | |
Yamada et al. | Dynamical linking of positive and negative sentences to goal-oriented robot behavior by hierarchical rnn | |
Kakemoto et al. | Deep neural network for dynamic symbol | |
Kar et al. | Artificial neural networks and learning techniques | |
Feofilov et al. | Features of Synthesis of Neural Network Simulators with Limiters | |
Lin et al. | The Stereo Neural Network: The Mathematical Architecture and Weight Optimization | |
Shibata et al. | katsunarishibata@ gmail. com Oita University | |
Shilpa Mehta et al. | A COMPREHENSIVE STUDY OF NEURAL NETWORK ARCHITECTURE AND FUNCTIONALITY |