Robust Stability of Uncertain Cellular Neural Networks with Time-Varying Delays


In this paper, we investigate the problem of global robust asymptotical stability of cellular neural networks with time-varying delays and parameter uncertainties. The parameter uncertainties are assumed to be bounded, the activation functions are supposed to be bounded and globally Lipschitz continuous. Based on the Lyapunov-Krasovskii functional approach, a new delay-dependent stability criteria is presented in terms of linear matrix inequalities (LMIs). The stability criteria can be easily checked by using recently developed algorithms in solving LMIs. Finally, a numerical example is given to illustrate the effectiveness and less conservativeness of our proposed method.

DOI: 10.1109/SNPD.2007.326

Cite this paper

@article{Su2007RobustSO, title={Robust Stability of Uncertain Cellular Neural Networks with Time-Varying Delays}, author={Lian-Qing Su and Zhifeng Gao and Jiqing Qiu and Peng Shi}, journal={Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007)}, year={2007}, volume={3}, pages={423-426} }