Absolute Exponential Stability of a Class of Neural Networks
نویسندگان
چکیده
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 the neural system is AEST.
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