作者: Tao Li , Lei Guo , Lingyao Wu , Changyin Sun
DOI: 10.1007/S12555-009-0214-8
关键词: Linear matrix 、 Stability (probability) 、 Linear matrix inequality 、 Artificial neural network 、 Term (time) 、 Mathematics 、 Control theory 、 Delay dependent 、 Control and Systems Engineering 、 Computer Science Applications
摘要: This article investigates the problem of robust stability for neural networks with time-varying delays and parameter uncertainties linear fractional form. By introducing a new Lyapunov-Krasovskii functional tighter inequality, delay-dependent criteria are established in term matrix inequalities (LMIs). It is shown that obtained can provide less conservative results than some existing ones. Numerical examples given to demonstrate applicability proposed approach.