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This article is cited in 6 scientific papers (total in 6 papers)
Synchronization of Heteroclinic Circuits through Learning in Coupled Neural Networks
Anton Selskiia, Valeri A. Makarovab a N.I. Lobachevsky State University of Nizhny Novgorod, ul. Gagarina 23, Nizhny Novgorod, 603950, Russia
b Instituto de Matemática Interdiciplinar, F. CC. Matemáticas, Universidad Complutense de Madrid, Madrid, 28040, Spain
Abstract:
The synchronization of oscillatory activity in neural networks is usually implemented by coupling the state variables describing neuronal dynamics. Here we study another, but complementary mechanism based on a learning process with memory. A driver network, acting as a teacher, exhibits winner-less competition (WLC) dynamics, while a driven network, a learner, tunes its internal couplings according to the oscillations observed in the teacher. We show that under appropriate training the learner can “copy” the coupling structure and thus synchronize oscillations with the teacher. The replication of the WLC dynamics occurs for intermediate memory lengths only, consequently, the learner network exhibits a phenomenon of learning resonance.
Keywords:
synchronization, learning, heteroclinic circuit, neural networks, winner-less competition.
Received: 25.08.2015 Accepted: 01.09.2015
Citation:
Anton Selskii, Valeri A. Makarov, “Synchronization of Heteroclinic Circuits through Learning in Coupled Neural Networks”, Regul. Chaotic Dyn., 21:1 (2016), 97–106
Linking options:
https://www.mathnet.ru/eng/rcd68 https://www.mathnet.ru/eng/rcd/v21/i1/p97
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