|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|147777||2018||11 صفحه PDF||سفارش دهید||9044 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Neurocomputing, Volume 284, 5 April 2018, Pages 160-170
In this paper, the problem of feedback controller designed to achieve adaptive exponential stabilization is investigated for stochastic neural networks of neutral type with Markovian switching parameters and the noise characterised by LÃ©vy process. Based on Lyapunov functional theory and the generalized ItÃ´s formula for neutral-type systems, the goal of this paper is to derive some criteria to ensure adaptive exponential stabilization for the stochastic neutral-type neural networks. Moreover, the update law of the control gain and the dynamic variation of the parameters of the system are provided. Finally, the theoretical analysis and potential of the stabilization criteria proposed in this paper are verified by a numerical example.