FIELD: physics.
SUBSTANCE: invention relates to bionics, modelling human functional aspects and can be used in computer engineering when constructing intelligent machines and systems. Substance of the method consists in that the signal is supplied to a multilayer recurrent neural network, in which at each k+1 processing level of neuron excitation threshold and amplitude of single images formed by them is more than their values at k-level. Additionally, intersecting preset length of sample from sequence of processed sets of unit images of k-level is converted to a set of single images k+1 level and each of them is associated with corresponding sample. Treating additionally formed sets of single images at k+1 level similarly to processing of signal at k- level and connecting them in space and time through memorizing links on network elements. These links are used to extract signals from memory. Treated sets of unit images of k+1 level are converted back into corresponding combined samples of sequences of sets of single images of the kth level. These samples are used to generate signal processing results in a network.
EFFECT: high intelligence of processing information in a neural network, improved recognition, memorizing, generation of new useful signals and retrieval thereof from network memory.
1 cl, 7 dwg
