A study on state estimation for discrete-time recurrent neural networks with leakage delay and time-varying delay

Advances in Difference Equations

Xin-Ge Liu¹  Yan-Jun Shu²  Sai-Bing Qiu² 

[1] College of Mathematics and Computer Science, Hunan City University, Yiyang, P.R. China;School of Mathematics and Statistics, Central South University, Changsha, P.R. China

关键词: state estimation;    discrete-time;    leakage delay;    stability;   

DOI  :  10.1186/s13662-016-0958-4

学科分类：数学（综合）

来源: SpringerOpen

【 摘 要 】

We investigate state estimation for a class of discrete-time recurrent neural networks with leakage delay and time-varying delay. The design method for the state estimator to estimate the neuron states through available output measurements is given. A novel delay-dependent sufficient condition is obtained for the existence of state estimator such that the estimation error system is globally asymptotically stable. Based a novel double summation inequality and reciprocally convex approach, an improved stability criterion is obtained for the error-state system. Two numerical examples are given to demonstrate the effectiveness of the proposed design methods. The simulation results show that the leakage delay has a destabilizing influence on a neural network system.

【 授权许可】

CC BY