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Neural Processing Letters

, Volume 47, Issue 1, pp 203–232 | Cite as

Delta-Differentiable Weighted Pseudo-Almost Automorphicity on Time–Space Scales for a Novel Class of High-Order Competitive Neural Networks with WPAA Coefficients and Mixed Delays

Article

Abstract

In this paper, we consider a novel class of high-order competitive neural networks with mixed delays. Different from the previous literature, we study the existence and exponential stability of weighted pseudo-almost automorphic on time–space scales solutions for the suggested system. Our method is mainly based on the Banach’s fixed point theorem, the theory of calculus on time scales and the Lyapunov–Krasovskii functional method. Moreover, a numerical example is given to show the effectiveness of the main results.

Keywords

Time scales High-order competitive neural networks Weighted pseudo-almost automorphic solution Global exponential stability Leakage delays 

Notes

Acknowledgements

The authors would like to express their sincere thanks to the referees for suggesting some corrections that help making the content of the paper more accurate.

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.Department of Mathematics, Physics and Computer Science, Higher Institute of Applied Sciences and Technology of KairouanUniversity of KairouanKairouanTunisia
  2. 2.Laboratory of Engineering Mathematics (LR01ES13), Tunisia Polytechnic SchoolUniversity of CarthageCarthageTunisia
  3. 3.Nonlinear Analysis and Applied Mathematics (NAAM) Research Group, Department of MathematicsKing Abdulaziz UniversityJeddahSaudi Arabia
  4. 4.School of Mathematics, and Research Center for Complex Systems and Network SciencesSoutheast UniversityNanjingChina
  5. 5.Department of Mathematics, Faculty of ScienceKing Abdulaziz UniversityJeddahSaudi Arabia

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