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Global asymptotic stability of high-order Hopfield type neural networks with time delays. (English) Zbl 1045.37056

Summary: This paper studies the global asymptotic stability of a class of high-order Hopfield-type neural networks with time delays. By utilizing Lyapunov functionals, we obtain some sufficient conditions for the global asymptotic stability of the equilibrium point of such neural networks in terms of linear matrix inequality. Numerical examples are given to illustrate the advantages of our approach.

MSC:

37N20 Dynamical systems in other branches of physics (quantum mechanics, general relativity, laser physics)
34D23 Global stability of solutions to ordinary differential equations
82C32 Neural nets applied to problems in time-dependent statistical mechanics
68T05 Learning and adaptive systems in artificial intelligence
94A08 Image processing (compression, reconstruction, etc.) in information and communication theory
94A12 Signal theory (characterization, reconstruction, filtering, etc.)
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