DocumentCode :
1341507
Title :
New Passivity Analysis for Neural Networks With Discrete and Distributed Delays
Author :
Hongyi Li ; Huijun Gao ; Peng Shi
Author_Institution :
Inst. of Intell. Control & Syst., Harbin Inst. of Technol., Harbin, China
Volume :
21
Issue :
11
fYear :
2010
Firstpage :
1842
Lastpage :
1847
Abstract :
In this brief, the problem of passivity analysis is investigated for a class of uncertain neural networks (NNs) with both discrete and distributed time-varying delays. By constructing a novel Lyapunov functional and utilizing some advanced techniques, new delay-dependent passivity criteria are established to guarantee the passivity performance of NNs. Essentially different from the available results, when estimating the upper bound of the derivative of Lyapunov functionals, we consider and best utilize the additional useful terms about the distributed delays, which leads to less conservative results. These criteria are expressed in the form of convex optimization problems, which can be efficiently solved via standard numerical software. Numerical examples are provided to illustrate the effectiveness and less conservatism of the proposed results.
Keywords :
Lyapunov methods; delays; discrete time systems; neural nets; time-varying systems; uncertain systems; Lyapunov functional; convex optimization; delay dependent passivity criteria; discrete delay; distributed delay; numerical software; passivity analysis; time varying delays; uncertain neural network; Artificial neural networks; Delay; Delay effects; Linear matrix inequalities; Stability criteria; Symmetric matrices; Distributed delays; neural networks (NNs); passivity; time-varying delays; Algorithms; Artificial Intelligence; Mathematical Computing; Neural Networks (Computer); Software Design; Software Validation; Time Factors;
fLanguage :
English
Journal_Title :
Neural Networks, IEEE Transactions on
Publisher :
ieee
ISSN :
1045-9227
Type :
jour
DOI :
10.1109/TNN.2010.2059039
Filename :
5593884
Link To Document :
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