论文信息 - LMI-Based Approach for Global Asymptotic Stability Analysis of Discrete-Time Cohen-Grossberg Neural Networks

LMI-Based Approach for Global Asymptotic Stability Analysis of Discrete-Time Cohen-Grossberg Neural Networks

The global asymptotic stability of discrete-time Cohen---Grossberg neural networks (CGNNs) with or without time delays is studied in this paper. The CGNNs are transformed into discrete-time interval systems, and several sufficient conditions of asymptotic stability for these interval systems are derived by constructing some suitable Lyapunov functionals. The obtained conditions are given in the form of linear matrix inequalities that can be checked numerically and very efficiently by resorting to the MATLAB LMI Control Toolbox.

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