Abstract

In this paper, the problem of the global dissipativity of high-order Hopfield bidirectional associative memory neural networks with time-varying coefficients and distributed delays is discussed. By using Lyapunov–Krasovskii functional method, inequality techniques and linear matrix inequalities, a novel set of sufficient conditions for global dissipativity and global exponential dissipativity for the addressed system is developed. Further, the estimations of the positive invariant set, globally attractive set and globally exponentially attractive set are found. Finally, two examples with numerical simulations are provided to support the feasibility of the theoretical findings.

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