Robust Stability of Time-Delayed Interval CNN in Noisy Environment
噪声环境中时延区间CNN网络鲁棒稳定性

Because of the VLSI realization of cellular neural networks (CNN), noises coming from the circuit are unavoidable and therefore any real CNNs operate in a noisy environment. It is very important to understand how these stochastic perturbations affect the networks' stability in system synthesis. Making use of the martingale convergence theorem, Lyapunov direct methods and matrix analysis, the tolerance against perturbations for the time-delays interval cellular neural networks (ICNN) perturbed by white noise is examed, and some sufficiently algebraic criteria which only depend on the systems' parameters are given. The results obtained in this paper are easily tested in system synthesis.