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Abstract: This paper deals with the exponential synchronization problem for a class of stochastic jumping chaotic neural networks with mixed delays and sector bounded nonlinearities. The mixed time delays under consideration comprise both discrete time-varying delays and distributed time delays. By applying the Finsler’s Lemma and constructing appropriate Lyapunov–Krasovskii functional based on delay partitioning, several improved delay-dependent feedback controllers with sector nonlinearities are developed to achieve the synchronization in mean square in terms of linear matrix inequalities. It is established theoretically that two special cases of the obtained criteria are less conservative than some existing results but including fewer slack variables. As the present conditions involve no free weighting matrices, the computational burden is largely reduced. One numerical example is provided to demonstrate the effectiveness of the theoretical results. [Copyright &y& Elsevier]

Abstract: A novel method is proposed for existence, uniqueness, asymptotic stability of certain and uncertain cellular neural networks with interval time-varying delays. By introducing triple-integral terms, a new Lyapunov functional is established. Without assuming the boundedness and monotonicity of activation functions, by applying homeomorphism mapping theorem, Jensen integral inequality and generalized Jensen integral inequality, new delay-dependent stability criteria are obtained with some free-weighting matrices involved. Since the results are presented in terms of linear matrix inequalities, the conditions can be solved efficiently by using the recently developed interior-point algorithm. Finally, four examples are also given to illustrate the effectiveness and less conservativeness of the proposed criteria. [Copyright &y& Elsevier]