Robust filtering of uncertain stochastic genetic regulatory networks with time-varying delays

This study is concerned with the problem of robust filtering for stochastic genetic regulatory networks with time-varying delays and parameter uncertainties. By choosing an appropriate novel Lyapunov-Krasovskii functional and establishing a new integral inequality in the stochastic setting, less conservative conditions are obtained to ensure the error systems are mean-square robustly asymptotically stable. Then the filters are designed in terms of linear matrix inequalities (LMIs) which can be checked efficiently via the LMI tool-box. What is more, the criteria can be applicable to both fast and slow time-varying delays due to our careful consideration of the ranges for the time-varying delays. Finally, two examples are presented to illustrate the effectiveness and advantages of the theoretical results. (C) 2012 Elsevier Ltd. All rights reserved.