Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
409199 | Neurocomputing | 2014 | 9 Pages |
This paper addresses the problem of robust H∞H∞ filter design for a class of stochastic Markovian jump Hopfield neural networks with mode-dependent time-varying delays and norm-bounded parameter uncertainties. The purpose is to design a mode-dependent linear filtering which ensures that, for all admissible uncertainties, the filtering error system is not only stochastically asymptotically stable in the large, but also satisfies a prescribed H∞-normH∞-norm level. Some novel mode-dependent and delay-dependent sufficient conditions for the solvability of this problem are obtained. The desired filter can be constructed by solving a set of strict linear matrix inequalities. A numerical example is provided to illustrate the effectiveness of the proposed method.