Delay-dependent stability criteria for network-based neural networks
网络化神经网络的时滞依赖稳定性判据(英文)

This paper investigates the problem of stability of network-based neural networks (NNs). To exploit the sampling characteristic of network systems, we define a new type of Lyapunov functional. By analyzing the relation between the network-induced delay and the executive duration, and employing an iterative convex combination technique, we develop a less conservative stability criterion for network-based NNs. To reduce the computational complexity, we also propose a stability criterion for sampled-data-based NNs. An illustrative example is given to show the effectiveness and the advantages of the proposed method.