Global Exponential Stability for Neutral-type Uncertain Dynamic Neural Networks With Hybrid Time-varying Delays
Time delays often occur in many industrial systems, and may deteriorate system performance or even cause instability. Therefore, stability analysis is important for the systems. The global exponential stability was discussed for the neutral-type uncertain dynamic neural networks with hybrid timevarying d-elays. Without assuming the bounedness of the activation function, and the parameter uncertainties are assumed to be norm bounded. Based on the Lyapunov-Krasovskii functional stability analysis and the linear matrix inequality (LMI) approach, a new sufficient condition was derived. Which generalize the previous results in the literature and has less conservative.
time delays neutral-type uncertain Lyapunov functional LMI stability
Liang Wu Lei Zhao Jiefang Liu Yingfeng Zhao
Henan Institute of Science and Technology, Department of Mathematics, Henan Xinxiang 453003 China
国际会议
武汉
英文
655-659
2010-06-06（万方平台首次上网日期，不代表论文的发表时间）