Global dissipativity analysis for memristor-based uncertain neural networks with time delay in the leakage term

Regular Papers Intelligent Control and Applications
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Abstract

This paper is concerned with the problem of global dissipativity analysis for a class of memristor-based uncertain neural networks with leakage delay and state-dependent switched memductance functions. By combining differential inclusions with set-valued maps and constructing a proper Lyapunov-Krasovskii functional, delaydependent criteria in terms of linear matrix inequalities are obtained for the global dissipativity of the memristive uncertain neural networks. Finally, a numerical example is given to illustrate the feasibility of the theoretical results.

Keywords

Differential inclusions golbal dissipativity leakage delay memristor-based neural networks uncertain 

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Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Institute of Applied MathematicsShijiazhuang Mechanical Engineering CollegeShijiazhuang, HebeiP. R. China

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