FIELD: neuro-cybernetics, possible use in artificial neuron networks for solving various problems of logical processing of binary data.
SUBSTANCE: method for realization of logical nonequivalence function by neuron with two inputs is based on multiplication of input signals with corresponding weight coefficients and summing them, after that the total is transformed in activation block firstly by quadratic transfer function, and then by threshold function at neuron output.
EFFECT: realization by one neuron of first order of logical nonequivalence function of two variables.
5 dwg, 1 tbl
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| NEURON MODEL, REALIZING LOGICAL NONEQUIVALENCE FUNCTION | 2003 |
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| NEURON SIMULATION METHOD | 2009 |
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| METHOD OF TRAINING ARTIFICIAL NEURAL NETWORK | 2014 |
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| METHOD FOR NOISELESS GRADIENT SELECTION OF OBJECT CONTOURS ON DIGITAL IMAGES | 2015 |
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RU2589301C1 |
| METHOD OF NOISE-IMMUNE GRADIENT DETECTION OF CONTOURS OF OBJECTS ON DIGITAL IMAGES | 2008 |
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RU2360289C1 |
| CONTROL METHOD OF NEUROPROCESSOR RESPONSE TO INPUT SIGNALS | 2018 |
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RU2724784C2 |
| METHOD FOR NOISE-IMMUNE GRADIENT DETECTION OF OBJECT CONTOURS ON DIGITAL IMAGES | 2009 |
|
RU2403616C1 |
| NEURON SIMULATION OF REAL NEURON PROPERTIES | 2014 |
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RU2597495C2 |
| NEURON MODEL BASED ON DENDRITIC COMPUTING | 2021 |
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RU2777262C1 |
| NEAR-REAL IMPULSE NEURON | 2015 |
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RU2598298C2 |
