Sadanand et al., 2023 - Google Patents
Basic of Artificial Neural NetworkSadanand et al., 2023
View PDF- Document ID
- 5073322021403931170
- Author
- Sadanand D
- Bhosale S
- Publication year
- Publication venue
- Int. J. Adv. Res. Sci. Commun. Technol
External Links
Snippet
An information processing paradigm called an Artificial Neural Network (ANN) is based on how biological nervous systems, like the brain, process information. The information processing system's novel structure is the paradigm's most important feature. It is made up of …
- 238000013528 artificial neural network 0 title abstract description 69
Classifications
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- 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
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- 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
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- G—PHYSICS
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- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/04—Architectures, e.g. interconnection topology
- G06N3/049—Temporal neural nets, e.g. delay elements, oscillating neurons, pulsed inputs
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- G06N3/04—Architectures, e.g. interconnection topology
- G06N3/0454—Architectures, e.g. interconnection topology using a combination of multiple neural nets
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- G06N3/10—Simulation on general purpose computers
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- G06N5/04—Inference methods or devices
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- G—PHYSICS
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- G06N5/02—Knowledge representation
- G06N5/022—Knowledge engineering, knowledge acquisition
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- G—PHYSICS
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- 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
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- 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
- G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
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