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

被引:0
作者
黄玉娇
胡海根
机构
[1] CollegeofComputerScienceandTechnology,ZhejiangUniversityofTechnology
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
相关论文
共 6 条
[1]  
Impulsive effect on exponential synchronization of neural networks with leakage delay under sampled-data feedback control[J] . S. Lakshmanan,Ju H. Park,Fathalla A. Rihan,R. Rakkiyappan. Chinese Physics B . 2014 (7)
[2]  
Global stability of complex-valued neural networks with both leakage time delay and discrete time delay on time scales[J] . Xiaofeng Chen,Qiankun Song. Neurocomputing . 2013
[3]  
Dynamical stability analysis of multiple equilibrium points in time-varying delayed recurrent neural networks with discontinuous activation functions[J] . Yujiao Huang,Huaguang Zhang,Zhanshan Wang. Neurocomputing . 2012
[4]  
Analysis and design of associative memories based on recurrent neural network with discontinuous activation functions[J] . Gang Bao,Zhigang Zeng. Neurocomputing . 2011 (1)
[5]  
New results on stability criteria for neural networks with time-varying delays[J] . O.M. Kwon,J.W. Kwon,S.H. Kim. Chinese Physics B . 2011 (5)
[6]  
Linear matrix inequality approach for robust stability analysis for stochastic neural networks with time-varying delay[J] . S. Lakshmanan,P. Balasubramaniam. Chinese Physics B . 2011 (4)