Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6864573 | Neurocomputing | 2018 | 7 Pages |
Abstract
This paper is concerned with the l2âlâ state estimation problem for discrete-time switched neural networks with time-varying delay. The main objective is to design a mode-dependent state estimator such that the error dynamics is exponentially stable with a weighted l2âlâ performance level. By incorporating the novel l2âlâ performance analysis approach, the augmented piecewise Lyapunov-like functionals, the discrete Wirtinger-based inequality and the average-dwell-time switching, less conservative sufficient conditions are proposed by means of linear matrix inequalities. A numerical example is given to illustrate the effectiveness and benefits of the obtained results.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Yonggang Chen, Lili Liu, Wei Qian, Yurong Liu, Fuad E. Alsaadi,