Exponential stability of high-order stochastic Hopfield-type neuralnetworks with time-varying delays and distributed parameters
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    Abstract:

    In this paper,a generalized stochastic model of high-order Hopfield-typeneural networks with time-varying delays and distributed parametersis considered.The sufficientconditions ensuring the exponential stability of the systems are developed by using Lyapunovstability theory,an integral inequality and Halanay's inequality.The proposed conditions are diffusion-dependent due to the use of the new integral inequality.As a result,the obtained conditions may have some advantages over the those previously reported.As anillustration,an numerical example is worked out using the resultsobtained.

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ZHAO Birong, DAI Xisheng. Exponential stability of high-order stochastic Hopfield-type neuralnetworks with time-varying delays and distributed parameters[J]. Journal of Nanjing University of Information Science & Technology,2014,6(2):182-187

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  • Received:February 18,2014
  • Online: April 21,2014
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