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A New Method of the Pattern Storage and Recognition in Oscillatory Neural Networks Based on Resistive Switches

Institute of Physics and Technology, Petrozavodsk State University, 31 Lenina str., Petrozavodsk 185910, Russia
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Electronics 2018, 7(10), 266; https://doi.org/10.3390/electronics7100266
Received: 10 September 2018 / Revised: 16 October 2018 / Accepted: 18 October 2018 / Published: 22 October 2018
(This article belongs to the Special Issue Nanoelectronic Materials, Devices and Modeling)
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Abstract

Development of neuromorphic systems based on new nanoelectronics materials and devices is of immediate interest for solving the problems of cognitive technology and cybernetics. Computational modeling of two- and three-oscillator schemes with thermally coupled VO2-switches is used to demonstrate a novel method of pattern storage and recognition in an impulse oscillator neural network (ONN), based on the high-order synchronization effect. The method allows storage of many patterns, and their number depends on the number of synchronous states Ns. The modeling demonstrates attainment of Ns of several orders both for a three-oscillator scheme Ns ~ 650 and for a two-oscillator scheme Ns ~ 260. A number of regularities are obtained, in particular, an optimal strength of oscillator coupling is revealed when Ns has a maximum. Algorithms of vector storage, network training, and test vector recognition are suggested, where the parameter of synchronization effectiveness is used as a degree of match. It is shown that, to reduce the ambiguity of recognition, the number coordinated in each vector should be at least one unit less than the number of oscillators. The demonstrated results are of a general character, and they may be applied in ONNs with various mechanisms and oscillator coupling topology. View Full-Text
Keywords: oscillatory neural networks; pattern recognition; higher order synchronization; thermal coupling; vanadium dioxide oscillatory neural networks; pattern recognition; higher order synchronization; thermal coupling; vanadium dioxide
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Velichko, A.; Belyaev, M.; Putrolaynen, V.; Boriskov, P. A New Method of the Pattern Storage and Recognition in Oscillatory Neural Networks Based on Resistive Switches. Electronics 2018, 7, 266.

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