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This paper investigates the absolute exponential stability (AEST) of a class of neural networks with a general class of partially Lipschitz continuous and monotone increasing activation functions. The main obtained result is that if the interconnection matrix T of the neural system satisfies that T − is an H -matrix with nonnegative diagonal elements, then(More)
In this brief, based on Lyapunov-Krasovskii functional approach and appropriate integral inequality, a new sufficient condition is derived to guarantee the global stability for delayed neural networks with unbounded distributed delay, in which the improved delay-partitioning technique and general convex combination are employed. The LMI-based criterion(More)
In this paper, we address, in a backstepping way, stabilization problem for a class of switched nonlinear systems whose subsystem with trigonal structure by using neural network. An adaptive neural network switching control design is given. Backsteppping, domination and adaptive bounding design technique are combined to construct adaptive neural network(More)
In this paper, we deal with the exponential synchronization problem for a class of chaotic neural networks with mixed delays and impulsive effects via output coupling with delay feedback. The mixed delays in this paper include time-varying delays and unbounded distributed delays. By using a Lyapunov–Krasovski˘ ı functional, a drive–response concept and a(More)