title: Robust stochastic stability of discrete-time fuzzy Markovian jump neural networks.
abstract: This paper focuses the issue of robust stochastic stability for a class of uncertain fuzzy Markovian jumping discrete-time neural networks (FMJDNNs) with various activation functions and mixed time delay. By employing the Lyapunov technique and linear matrix inequality (LMI) approach, a new set of delay-dependent sufficient conditions are established for the robust stochastic stability of uncertain FMJDNNs. More precisely, the parameter uncertainties are assumed to be time varying, unknown and norm bounded. The obtained stability conditions are established in terms of LMIs, which can be easily checked by using the efficient MATLAB-LMI toolbox. Finally, numerical examples with simulation result are provided to illustrate the effectiveness and less conservativeness of the obtained results.
authors.affiliation: Department of Mathematics, Anna University-Regional Centre, Coimbatore 641047, India.
authors.forename: A
authors.initials: A
authors.lastname: Arunkumar
authors.affiliation: Department of Mathematics, Sri Ramakrishna Institute of Technology, Coimbatore 641010, India; Department of Mathematics, Sungkyunkwan University, Suwon 440-746, South Korea. Electronic address: krsakthivel@yahoo.com.
authors.forename: R
authors.initials: R
authors.lastname: Sakthivel
authors.affiliation: Nonlinear Dynamics Group, Department of Electrical Engineering, Yeungnam University, 280 Daehak-Ro, Kyongsan 712-749, Republic of Korea.
authors.forename: K
authors.initials: K
authors.lastname: Mathiyalagan
authors.affiliation: Nonlinear Dynamics Group, Department of Electrical Engineering, Yeungnam University, 280 Daehak-Ro, Kyongsan 712-749, Republic of Korea.
authors.forename: Ju H
authors.initials: JH
authors.lastname: Park
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D005246:Feedback; D017143:Fuzzy Logic; D008390:Markov Chains; D015233:Models, Statistical; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D013269:Stochastic Processes
keywords: Discrete-time neural networks; Linear matrix inequality; Markovian jump; Stochastic stability; Various activation functions