New exponential passivity of BAM neural networks with time-varying delays

被引:5
|
作者
Thipcha, J. [1 ]
Niamsup, P. [1 ]
机构
[1] Chiang Mai Univ, Dept Math, Chiang Mai 50200, Thailand
来源
NEURAL COMPUTING & APPLICATIONS | 2018年 / 29卷 / 12期
关键词
BAM neural networks; Exponential passivity; Linear matrix inequality (LMI); Time-varying delays; GLOBAL ASYMPTOTIC STABILITY; CRITERIA;
D O I
10.1007/s00521-016-2657-1
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, the exponential passivity for bidirectional associative memory (BAM) neural networks with time-varying delays is considered. In our study, the lower and upper bounds of the activation functions are allowed to be either positive, negative or zero. By constructing new and improved Lyapunov-Krasovskii functional and introducing free-weighting matrices, a new and improved delay-dependent exponential passivity criterion for BAM neural networks with time-varying delays is derived in the form of linear matrix inequality (LMI). A numerical example is given to show that the derived condition is less conservative than some existing results given in the literature.
引用
收藏
页码:1593 / 1600
页数:8
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