Extended dissipative analysis of delayed stochastic Markovian jump neural networks

被引：0
|
作者：
Chen, Guoliang [1 ]
Xia, Jianwei [1 ]
Gao, Hui [1 ]
机构：
[1] Liaocheng Univ, Sch Math Sci, Liaocheng 252000, Peoples R China
来源：
PROCEEDINGS OF THE 28TH CHINESE CONTROL AND DECISION CONFERENCE (2016 CCDC) | 2016年
关键词：
Dissipativity; Delayed stochastic Markovian jump neural networks; Stability; TIME-VARYING DELAYS; ROBUST STABILITY ANALYSIS; EXPONENTIAL STABILITY; PARAMETERS; SYSTEMS;
D O I：
暂无
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 brief, an extended dissipativity analysis is developed for a delayed stochastic Markovian jump neural networks(DSMNNs). Based on the concept of the extended dissipative, H-infinity, L-2 - L-infinity, the passive and dissipative performance are solved by adjusting the weighting matrices in a new performance index. In addition, two different methods are applied to deal with the stochastic cross terms containing Ito integral.
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页码：5903 / 5908
页数：6
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