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Ultimate boundedness and an attractor for stochastic Hopfield neural networks with time-varying delays. (English) Zbl 1238.34145
Summary: We investigates ultimate boundedness and a weak attractor for stochastic Hopfield neural networks (HNN) with time-varying delays. By employing the Lyapunov method and the matrix technique, some novel results and criteria on ultimate boundedness and an attractor for stochastic HNN with time-varying delays are derived. Finally, a numerical example is given to illustrate the correctness and effectiveness of our theoretical results.
MSC:
34K50Stochastic functional-differential equations
34K12Growth, boundedness, comparison of solutions of functional-differential equations
34D45Attractors
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