Global exponential dissipativity of neutral-type BAM inertial neural networks with mixed time-varying delays

Abstract This paper considers the global exponential dissipativity of neutral-type BAM inertial neural networks with mixed time-varying delays. Firstly, we transform the proposed BAM inertial neural networks to usual one. Secondly, by establishing a new neutral-type differential inequality and employing Lyapunov method and analytical techniques, some novel sufficient conditions in accordance with algebraic and linear matrix inequalities are obtained for the global exponential dissipativity of the addressed neural networks. Moreover, the globally exponentially attractive sets and the exponential convergence rate index are also assessed. Finally, the effectiveness of the obtained results is illustrated by some examples with numerical simulations.

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