Multistability of delayed complex-valued recurrent neural networks with discontinuous real-imaginary-type activation functions

doi:10.1088/1674-1056/24/12/120701

Abstract

In this paper, the multistability issue is discussed for delayed complex-valued recurrent neural networks with discontinuous real-imaginary-type activation functions. Based on a fixed theorem and stability definition, sufficient criteria are established for the existence and stability of multiple equilibria of complex-valued recurrent neural networks. The number of stable equilibria is larger than that of real-valued recurrent neural networks, which can be used to achieve high-capacity associative memories. One numerical example is provided to show the effectiveness and superiority of the presented results.

Keywords: complex-valued recurrent neural network discontinuous real-imaginary-type activation function multistability delay

Received: 12 May 2015
Revised: 27 June 2015
Accepted manuscript online:

PACS:	07.05.Mh	(Neural networks, fuzzy logic, artificial intelligence)
	02.30.Ks	(Delay and functional equations)

Fund:

Project supported by the National Natural Science Foundation of China (Grant Nos. 61374094 and 61503338) and the Natural Science Foundation of Zhejiang Province, China (Grant No. LQ15F030005).

Corresponding Authors: Huang Yu-Jiao
E-mail: hyj0507@zjut.edu.cn

Cite this article:

Huang Yu-Jiao (黄玉娇), Hu Hai-Gen (胡海根) Multistability of delayed complex-valued recurrent neural networks with discontinuous real-imaginary-type activation functions 2015 Chin. Phys. B 24 120701

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Multistability of delayed complex-valued recurrent neural networks with discontinuous real-imaginary-type activation functions

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