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Abstract
This paper investigates the problem of mean-square finite-time passivity of discrete-time stochastic Markov jump neural networks with distributed delays and sensor nonlinearities. The distributed delays and sensor nonlinearities are randomly varying and described by mode-dependent random sequences with known statistical information. The mean-square finite-time boundedness and mean-square finite-time passivity results are obtained based on Lyapunov-like functional method. And the mean-square finite-time passivity is also considered for neural networks with random infinite-distributed delays. Finally, a numerical example verifies the effectiveness of the method.
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