Novel stability of cellular neural networks with interval time-varying delay. (English) Zbl 1254.34102
Summary: In this paper, the asymptotic stability is investigated for a class of cellular neural networks with interval time-varying delay (that is, \(0<h_{1}<d(t)<h_{2}\)). By introducing a novel Lyapunov functional with the idea of partitioning the lower bound \(h_{1}\) of the time-varying delay, a new criterion of asymptotic stability is derived in terms of a linear matrix inequality (LMI), which can be efficiently solved via standard numerical software. The criterion proves to be less conservative than most of the existing results, and the conservatism could be notably reduced by thinning the delay partitioning. Two examples are provided to demonstrate the less conservatism and effectiveness of the proposed stability conditions.
MSC:
| 34K20 | Stability theory of functional-differential equations |
| 39A30 | Stability theory for difference equations |
| 34K25 | Asymptotic theory of functional-differential equations |
| 34K60 | Qualitative investigation and simulation of models involving functional-differential equations |
Keywords:
cellular neural networks; delay partitioning; global asymptotic stability; interval time-varying delay; linear matrix inequalityReferences:
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