Title :
Generalized H2 State estimation of stochastic neural networks with time-varying delay
Author :
Mingang Hua ; Jianyong Zhang ; Juntao Fei
Author_Institution :
Coll. of Comput. & Inf., Hohai Univ., Changzhou, China
Abstract :
The generalized H2 state estimation problem for stochastic neural networks is considered int this paper. The delay-dependent design criterion is established such that the error system is asymptotical mean-square stable with a prescribed generalized H2 performance. The gain matrix and the optimal performance index are obtained by solving a generalized eigenvalue problem. Numerical example is given to show the effectiveness of the proposed design methods.
Keywords :
H∞ control; asymptotic stability; delay systems; eigenvalues and eigenfunctions; matrix algebra; neurocontrollers; stochastic systems; asymptotic stability; delay-dependent design; gain matrix; generalized H2 state estimation; generalized eigenvalue problem; mean-square stability; optimal performance index; stochastic neural network; time-varying delay; Biological neural networks; Delays; Estimation error; Neurons; State estimation; Trajectory; Asymptotical mean-square stability; Generalized H2 state estimation; Linear matrix inequalities; Stochastic neural networks; Time-varying delay;
Conference_Titel :
SICE Annual Conference (SICE), 2014 Proceedings of the
Conference_Location :
Sapporo
DOI :
10.1109/SICE.2014.6935256
