کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
405968 | 678051 | 2016 | 9 صفحه PDF | دانلود رایگان |
• Robust stability problem for discrete-time neural network with leakage delays is investigated.
• The random parameter uncertainties are characterized by Bernoulli distribution..
• Based on LKF method, sufficient conditions for stability are given in terms of LMIs
• Numerical simulations are exploited to illustrate the theoretical results.
This paper is concerned with the problem of robust stability analysis for discrete-time neural networks with time-varying coupling delays, random parameter uncertainties and time-varying leakage delays. The uncertainties enter into the system parameters in a random way and such randomly occurring uncertainties obey certain mutually uncorrelated Bernoulli-distributed white noise sequences. The important feature of the results reported here is that the probability of occurrence of the parameter uncertainties are known a priori. Constructing suitable Lyapunov–Krasovskii functional (LKF) terms, sufficient conditions ensuring the stability of the discrete-time neural networks are derived in terms of linear matrix inequalities (LMIs). Finally, numerical examples are rendered to exemplify the effectiveness of the proposed results.
Journal: Neurocomputing - Volume 179, 29 February 2016, Pages 126–134