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Finite-time H Filtering for Discrete-time Markovian Jump BAM Neural Networks with Time-varying Delays

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Abstract

This paper deals with the problem of finite-time H filtering for discrete-time Markovian jump BAM neural networks with time-varying delays. To do this, firstly by choosing a suitable Lyapunov function and using Jensen inequality lemma, sufficient criteria are derived to guarantee that the resulting filtering error system is finitetime bounded. And then the gain matrices of the controller and filter are achieved by solving a feasibility problem in terms of linear matrix inequalities with a fixed parameter. Moreover, we assume that disturbances are described by the jumping parameters are generated from discrete-time homogeneous Markov process. Finally a numerical example is presented to show the effectiveness of the proposed method.

Keywords

Bidirectional associative memory discrete time delay finite-time H control linear matrix inequality 

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Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of MathematicsThiruvalluvar UniversityVelloreIndia
  2. 2.School of IT Information and Control EngineeringKunsan National UniversityKunsanKorea

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