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Pseudo Almost Periodic Solution of Recurrent Neural Networks with D Operator on Time Scales

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Abstract

This paper is concerned with a class of neutral type recurrent neural networks with time-varying delays, distributed delay and D operator on time–space scales which unify the continuous-time and the discrete-time recurrent neural networks under the same framework. Some sufficient conditions are given for the existence and the global exponential stability of the pseudo almost periodic solution by using inequality analysis techniques on time scales, fixed point theorem and the theory of calculus on time scales. An example is given to show the effectiveness of the derived results via computer simulations.

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Authors and Affiliations

  1. Research Units of Mathematics and Applications UR13ES47, Department of Mathematics, Faculty of Sciences of Bizerta, University of Carthage, BP W, 7021, Zarzouna, Bizerta, Tunisia

    Chaouki Aouiti, El Abed Assali & Imen Ben Gharbia

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  1. Chaouki Aouiti
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  2. El Abed Assali
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  3. Imen Ben Gharbia
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Correspondence to Chaouki Aouiti.

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Aouiti, C., Assali, E.A. & Ben Gharbia, I. Pseudo Almost Periodic Solution of Recurrent Neural Networks with D Operator on Time Scales. Neural Process Lett 50, 297–320 (2019). https://doi.org/10.1007/s11063-019-10048-2

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