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Neural Computing and Applications

Erschienen in:

01.12.2013 | ISNN2012

Multistability of periodic delayed recurrent neural network with memristors

verfasst von: Gang Bao, Zhigang Zeng

Erschienen in: Neural Computing and Applications | Ausgabe 7-8/2013

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Abstract

This paper discusses the recurrent neural network (RNN) with memristors as connection weights. Memristor is a nonlinear resistor. Memristance varies periodically with time when the sinusoidal voltage source is applied. According to this property of memristor, it shows that coefficients of RNN with memristors are periodic functions with respect to time t. By dividing the state space and using contraction mapping theorem, one sufficient condition is obtained for multiperiodicity. And the periodic orbits located in saturation regions are locally exponentially stable limit cycles. At last, one example is given for verifying the validity of our result.

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Titel: Multistability of periodic delayed recurrent neural network with memristors
verfasst von: Gang Bao
Zhigang Zeng
Publikationsdatum: 01.12.2013
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 7-8/2013
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-012-0954-x

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