Title | ||
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An estimation of the domain of attraction for recurrent neural networks with time-varying delays |
Abstract | ||
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Based on Lyapunov-Krasovskii functional or Lyapunov-Razumikhin functional method and invariant set principle, we presented a new method to estimate the domain of attraction for general recurrent neural networks with time-varying delays. Convex optimization method is proposed to enlarge and estimate the domain of attraction. Local exponential stability conditions are derived, which can be expressed as linear matrix inequalities (LMIs) in terms of all the varying parameters and hence can be easily checked in both analysis and design. |
Year | DOI | Venue |
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2008 | 10.1016/j.neucom.2007.04.013 | Neurocomputing |
Keywords | Field | DocType |
local exponential stability condition,general recurrent neural network,linear matrix inequality,invariant set principle,convex optimization method,new method,varying parameter,time-varying delay,lyapunov-razumikhin functional method,recurrent neural network,neural network,convex optimization,recurrent neural networks,exponential stability | Mathematical optimization,Matrix (mathematics),Recurrent neural network,Exponential stability,Invariant (mathematics),Attraction,Convex optimization,Linear matrix inequality,Mathematics | Journal |
Volume | Issue | ISSN |
71 | 7-9 | Neurocomputing |
Citations | PageRank | References |
5 | 0.49 | 16 |
Authors | ||
4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Jun Xu | 1 | 31 | 3.33 |
Yong-Yan Cao | 2 | 1123 | 106.27 |
Daoying Pi | 3 | 50 | 9.21 |
Youxian Sun | 4 | 2707 | 196.15 |