Neural network comparing two-rate-encoded inputs entering in parallel.

J Pavlásek; T Hromádka

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PubMed · 11508822

Neural network comparing two-rate-encoded inputs entering in parallel.

J Pavlásek·T Hromádka

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Abstract

Presented computational model of a neural network is able to compare two regular input frequencies. The comparison is based on detection of inter-spike interval differences of the two frequencies. This detection is continuous and the network dynamically changes its output according to the changes in the input frequencies. The entire network is composed of biologically plausible parts. A combination of such simple comparators might be involved in the information processing in the central nervous system.

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Animals Central Nervous System Computers Humans Models, Theoretical Neural Networks, Computer Software Journal Article

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J Pavlásek, T Hromádka. 2001. Neural network comparing two-rate-encoded inputs entering in parallel.. https://pubmed.ncbi.nlm.nih.gov/11508822/

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