Stability Criterion for BAM Neural Networks of Neutral-Type with Interval Time-Varying Delays

被引：13
|
作者：
Liu, Guoquan [1 ]
Yang, Simon X. [1 ]
机构：
[1] Chongqing Univ, Coll Automat, Chongqing 400044, Peoples R China
来源：
CEIS 2011 | 2011年 / 15卷
关键词：
Asymptotic stability; Bidirectional associative memory neural networks; Neutral-type; Linear matrix inequality; Interval time-varying delays; BIDIRECTIONAL ASSOCIATIVE MEMORIES; GLOBAL EXPONENTIAL STABILITY; DISTRIBUTED DELAYS;
D O I：
10.1016/j.proeng.2011.08.534
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, the asymptotic stability for bidirectional associative memory (BAM) neural networks of neutral-type with interval time-varying delays is investigated. The discrete delay is assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. By employing the Lyapunov-Krasovskii functional method and using the linear matrix inequality (LMI) technique, a new delay-range-dependent stability criterion is established in terms of LMI. In addition, the proposed LMI based results can be easily checked by LMI control toolbox in Matlab. (c) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of [CEIS 2011]
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页数：5
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