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Global Exponential Stability in Lagrange Sense for Delayed Memristive Neural Networks with Parameter Uncertainties
  
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KeyWord:Memristive neural networks  Lagrange stability  Leakage delay  Uncertain parameters
Author NameAffiliation
Liangchen Li Institute of Applied Mathematics, Army Engineering University, Shijiazhuang, Hebei 050003, China 
Rui Xu Complex Systems Research Center, Shanxi University, Taiyuan, Shanxi 030006, China 
Jiazhe Lin Institute of Applied Mathematics, Army Engineering University, Shijiazhuang, Hebei 050003, China 
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Abstract:
      This paper addresses the Lagrange stability of memristive neural networks with leakage delay and time-varying transmission delays as well as parameter uncertainties. Based on the theory of Filippov's solution, by using Lyapunov-Krasovskii functionals and the free-weighting matrix method, sufficient conditions in terms of linear matrix inequality (LMI) are given to ascertain the networks with different kinds of activation functions to be stable in Lagrange sense. Meanwhile the estimation of globally attractive sets are given. Finally, numerical simulations are carried out to illustrate the effectiveness of theoretical results.