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Pseudo almost periodic solutions for neutral type high-order Hopfield neural networks with mixed time-varying delays and leakage delays on time scales

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We propose a class of neutral type high-order Hopfield neural networks with mixed time-varying delays and leakage delays on time scales. Applying the exponential dichotomy of linear dynamic equations on… Click to show full abstract

We propose a class of neutral type high-order Hopfield neural networks with mixed time-varying delays and leakage delays on time scales. Applying the exponential dichotomy of linear dynamic equations on time scales, Banach’s fixed point theorem and theory of calculus on time scales, we obtain several sufficient conditions to ensure the existence and global exponential stability of pseudo almost periodic solutions of the proposed neural networks. Finally, we illustrate the effectiveness of the obtained results with an example. The example also shows that the continuous-time neural network and its discrete-time analogue have the same dynamical behaviors when considering the pseudo almost periodicity.

Keywords: neural networks; time scales; neutral type; type high; time; pseudo almost

Journal Title: International Journal of Machine Learning and Cybernetics
Year Published: 2017

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