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

被引：0

作者：

黄玉娇 ^{[1
]}

胡海根 ^{[1
]}

机构：

[1] College of Computer Science and Technology, Zhejiang University of Technology

来源：

Chinese Physics B | 2015年 / 24卷 / 12期

基金：

中国国家自然科学基金;

关键词：

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

D O I：

暂无

中图分类号：

TP183 [人工神经网络与计算];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：275 / 283

页数：9

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