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Robust dissipativity and passivity analysis for discrete-time stochastic neural networks with time-varying delay

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Complexity 21 (3):47-58 (2016)

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  1. State estimation of memristor‐based recurrent neural networks with time‐varying delays based on passivity theory.R. Rakkiyappan,A. Chandrasekar,S. Laksmanan &Ju H. Park -2014 -Complexity 19 (4):32-43.
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  • Exponential state estimator design for discrete-time neural networks with discrete and distributed time-varying delays.Qihui Duan,Ju H. Park &Zheng-Guang Wu -2014 -Complexity 20 (1):38-48.
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  • Pinning sampled-data synchronization of complex dynamical networks with Markovian jumping and mixed delays using multiple integral approach.K. Sivaranjani &R. Rakkiyappan -2016 -Complexity 21 (S1):622-632.
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  • Robust Stability Criterion for Discrete-Time Nonlinear Switched Systems with Randomly Occurring Delays via T-S Fuzzy Approach.P. Balasubramaniam &L. Jarina Banu -2015 -Complexity 20 (6):49-61.
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