A delay‐dependent asymptotic stability criteria for uncertain BAM neural networks with leakage and discrete time‐varying delays: A novel summation inequality
C. Sowmiya, Ramachandran Raja, Jinde Cao, Grienggrai Rajchakit, Ahmed Alsaedi · Asian Journal of Control · 2019
Abstract This proposed research work aims to investigate the problem of uncertain BAM neural networks with leakage and discrete time‐varying delays in the sense of asymptotic stable by applying convex combination approach, discrete‐time Wirtinger inequality. It is pointed out that a novel summation inequality is entrenched based on discrete type Wirtinger based inequality. By the aid of novel inequality, reciprocally convex combination technique, time‐varying delays are examined to certify the stability of neural networks. Here, the uncertainties are considered as a randomly occurring parameter uncertainties and it conforms 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. To demonstrate the theoretical results of this research paper, numerical examples are given to expo the validity and efficiency of our results with the help of LMI Control toolbox in matlab.