title: Delay-distribution-dependent H∞state estimation for delayed neural networks with (x,v)-dependent noises and fading channels.
abstract: This paper deals with the H∞state estimation problem for a class of discrete-time neural networks with stochastic delays subject to state- and disturbance-dependent noises (also called (x,v)-dependent noises) and fading channels. The time-varying stochastic delay takes values on certain intervals with known probability distributions. The system measurement is transmitted through fading channels described by the Rice fading model. The aim of the addressed problem is to design a state estimator such that the estimation performance is guaranteed in the mean-square sense against admissible stochastic time-delays, stochastic noises as well as stochastic fading signals. By employing the stochastic analysis approach combined with the Kronecker product, several delay-distribution-dependent conditions are derived to ensure that the error dynamics of the neuron states is stochastically stable with prescribed H∞performance. Finally, a numerical example is provided to illustrate the effectiveness of the obtained results.
authors.affiliation: College of Information and Control Engineering, China University of Petroleum (East China), Qingdao 266580, China.
authors.forename: Li
authors.initials: L
authors.lastname: Sheng
authors.affiliation: College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, China; Department of Computer Science, Brunel University London, Uxbridge, Middlesex, UB8 3PH, United Kingdom. Electronic address: zidong.wang@brunel.ac.uk.
authors.forename: Zidong
authors.initials: Z
authors.lastname: Wang
authors.affiliation: School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing 210023, China.
authors.forename: Engang
authors.initials: E
authors.lastname: Tian
authors.affiliation: Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
authors.forename: Fuad E
authors.initials: FE
authors.lastname: Alsaadi
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D009474:Neurons; D009622:Noise; D011336:Probability; D013997:Time Factors
keywords:  state estimation; -dependent noises; Delay-distribution-dependent condition; Delayed neural networks; Fading channels; Random delay