ARTIFICIAL NEURAL NETWORK TRAINING METHOD Russian patent published in 2020 - IPC G06N3/08 

FIELD: information technology.

SUBSTANCE: invention refers to computer systems, namely to artificial neural networks (ANS), and can be used for training a neural network when simulating physical phenomena of technological processes. Method comprises the following operations: restricting the space of the input elements of the training sample by a certain area, sending to the inputs of the artificial neural network signals of training vectors and reference signals, the neuron synaptic weights vector is corrected, the training samples are formed based on consecutive application of the reference ANS, in the absence of a statistically sufficient number of observations of the analysed objects, generating input elements of training sampling u(n), n = 1, 2, …, K belonging to region O, for training an ANS, for ANS learning, selecting L reference ANS, training signal sampling u(n), n = 1, 2, …, K is sequentially sent to the input of each l^th reference ANS, and output signals , are recorded at its output, signals are converted to reference signals d_j(n), recording generated input elements of training sampling u(n) and reference signals d_j(n) corresponding to the subject solution with application of ANS problem, in the form of pairs 〈u(n), d_j(n)〉 on material carrier.

EFFECT: technical result is providing the possibility of training an ANS in the absence of a statistically sufficient number of observations of the analysed objects and reducing the time of ANS training.

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