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Exponential stabilization and synchronization of neural networks with time-varying delays via periodically intermittent control. (English) Zbl 1197.92005

Summary: A class of neural networks with time-varying delays are investigated for the first time using a periodically intermittent control technique. First, some new and useful stabilization criteria and synchronization conditions based on \(p\)-norms are derived by introducing multi-parameters and using Lyapunov functional techniques. For the \(\infty \)-norm, using analysis techniques, some novel conditions ensuring exponential stability and synchronization are also obtained. It is worth noting that the methods used in this paper are totally different from corresponding previous works and the obtained conditions are less conservative. Particularly, the traditional assumptions on control width and time delays are removed. Finally, some numerical simulations are given to verify the theoretical results.

MSC:

92B20 Neural networks for/in biological studies, artificial life and related topics
34K35 Control problems for functional-differential equations
34K20 Stability theory of functional-differential equations
65C20 Probabilistic models, generic numerical methods in probability and statistics
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