title: H∞state estimation for discrete-time neural networks with distributed delays and randomly occurring uncertainties through Fading channels.
abstract: In this paper, the H∞state estimation problem is investigated for a class of uncertain discrete-time neural networks subject to infinitely distributed delays and fading channels. Randomly occurring uncertainties (ROUs) are introduced to reflect the random nature of the network condition fluctuations, and the channel fading phenomenon is considered to account for the possibly unreliable network medium on which the measurement signal is transmitted. A set of Bernoulli-distributed white sequences are employed to govern the ROUs and the L-th Rice fading model is utilized where channel coefficients are mutually independent random variables with certain probability density function on [0,1]. We aim to design a state estimator such that the dynamics of the estimation error is asymptotically stable while satisfying the prescribed H∞performance constraint. By adopting the Lyapunov-Krasovskii functional and the stochastic analysis theory, sufficient conditions are established to ensure the existence of the desired state estimators and the explicit expression of such estimators is acquired. A simulation example is provided to verify the usefulness of the proposed approach.
authors.affiliation: College of Electrical and Information Engineering, Northeast Petroleum University, Daqing 163318, China.
authors.forename: Nan
authors.initials: N
authors.lastname: Hou
authors.affiliation: College of Electrical and Information Engineering, Northeast Petroleum University, Daqing 163318, China. Electronic address: shiningdhl@vip.126.com.
authors.forename: Hongli
authors.initials: H
authors.lastname: Dong
authors.affiliation: 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: College of Electrical and Information Engineering, Northeast Petroleum University, Daqing 163318, China.
authors.forename: Weijian
authors.initials: W
authors.lastname: Ren
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; D011897:Random Allocation; D013997:Time Factors; D035501:Uncertainty
keywords: Channel fadings; Infinitely distributed delays; Randomly occurring uncertainties; Recurrent neural networks; State estimation