Delay-Dependent Filtering of Static Neural NetworksWith Time-Varying Delay

摘要：

This paper is concerned with the generalized H2 filtering problem of static neural networks with time-varying delay. A delaydependent design criterion with less conservatism is derived by employing the reciprocally convex combination technique. It is shown that the gain matrix and the optimal generalized H2 performance index can be simultaneously obtained by solving a convex optimization problem subject to some linear matrix inequalities. An example is finally exploited to show the advantage of the developed condition over some existing results.

关键词： Static Neural Networks Time-Varying Delay Filtering Reciprocally Convex Combination Convex Optimization

作者: He Huang Xiaoping Chen

作者单位: School of Electronics and Information Engineering, Soochow University, Suzhou 215006, P. R. China

会议类型: 国际会议

会议名称: The 31st Chinese Control Conference(第三十一届中国控制会议)

会议地点: 合肥

会议语种:英文

页码: 3392-3397

在线出版日期: 2012-07-01（万方平台首次上网日期，不代表论文的发表时间）