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

作者：Qiu, Sai-Bing; Liu, Xin-Ge^*; Shu, Yan-Jun

来源：Advances in Difference Equations, 2016, 2016(1): 234.

DOI：10.1186/s13662-016-0958-4

• state estimation
• discrete-time
• leakage delay
• stability

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.

• 出版日期2016-9-7
• 单位湖南城市学院; 中南大学