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Global robust stability of interval cellular neural networks with time-varying delays. (English) Zbl 1101.68752

Summary: This paper studies the Global Robust Asymptotic Stability (GRAS) and Global Robust Exponential Stability (GRES) of delayed cellular neural networks with time-varying delays. A series of new criteria concerning GRAS and GRES are obtained by employing the Young’s inequality, Halanay’s inequality and Lyapunov functional and combine with some analysis techniques. Several previous results are improved and generalized. Some examples and remarks are also given to illustrate the effectiveness of the results. In addition, these criteria possess important leading significance in design and applications of global stable DCNNs, and are of great interest in many applications.

MSC:

68T05 Learning and adaptive systems in artificial intelligence
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