Name
Abstract | ||
|---|---|---|
In this paper, we continue to explore application of nonsmooth analysis to the study of global asymptotic robust stability (GARS) of delayed neural networks. In combination with Lyapunov theory, our approach gives several new types of sufficient conditions ensuring GARS. A significant common aspect of our results is their low computational complexity. It is demonstrated that the reported results c... |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/TCSI.2007.895524 | IEEE Transactions on Circuits and Systems I: Regular Papers |
Keywords | Field | DocType |
Sufficient conditions,Robust stability,Neural networks,Uncertainty,Symmetric matrices,Computational complexity,Neurons,Lyapunov method,Asymptotic stability | Lyapunov function,Mathematical optimization,Control theory,Equilibrium point,Symmetric matrix,Exponential stability,Artificial neural network,Mathematics,Semidefinite programming,Computational complexity theory | Journal |
Volume | Issue | ISSN |
54 | 5 | 1549-8328 |
Citations | PageRank | References |
29 | 1.30 | 12 |
Authors | ||
1 | ||