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 / 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
收藏
页码：275 / 283
页数：9
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