A state estimator of stochastic delayed neural networks

Abstract

The problem of state estimation for stochastic Hopfield neural networks with time-varying delay is investigated in this paper. Based on an auxiliary vector and free-weighting matrix technique, a delay-dependent Luenbergertype state estimator, which ensures mean-square asymptotic stability of the resulting filtering error state system, is designed. In this… (More)

Cite this paper

@article{Zhang2012ASE, title={A state estimator of stochastic delayed neural networks}, author={Chunxiao Zhang and Yun Chen and Junhong Wang}, journal={2012 24th Chinese Control and Decision Conference (CCDC)}, year={2012}, pages={2829-2832} }