Novel stability criterion for cellular neural networks: An improved Gu's discretized LKF approach
作者： Cheng-De Zheng , Qi-He Shan , Zhanshan Wang
DOI: 10.1016/J.JFRANKLIN.2011.09.014
关键词:
摘要: Abstract Novel stability criterion is presented for the existence, uniqueness and globally asymptotic of equilibrium point a class cellular neural networks with time-varying delays. Based on Gu's discretized Lyapunov–Krasovskii functional (LKF) theory, novel vector LKF introduced by dividing variation interval time delay into several subintervals equal length. By using homeomorphism mapping principle, free-weighting matrix method linear inequality (LMI) techniques, obtained condition less conservative than some previous results. Three examples are also given to show effectiveness criterion.
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