caa a22 4500 445360739 CHVBK 20180317142914.0 cr unu---uuuuu 170323e20110201xx s 000 0 eng 10.1007/s11071-010-9807-2 doi (NATIONALLICENCE)springer-10.1007/s11071-010-9807-2 Exponential stability for switched Cohen-Grossberg neural networks with average dwell time [Elektronische Daten] [Jie Lian, Kai Zhang] In this paper, uncertain switched Cohen-Grossberg neural networks with interval time-varying delay and distributed time-varying delay are proposed. Novel multiple Lyapunov functions are employed to investigate the stability of the switched neural networks under the switching rule with the average dwell time property. Sufficient conditions are obtained in terms of linear matrix inequalities (LMIs) which guarantee the exponential stability for the switched Cohen-Grossberg neural networks. Numerical examples are provided to illustrate the effectiveness of the proposed method. Springer Science+Business Media B.V., 2010 Switched systems nationallicence Cohen-Grossberg neural networks nationallicence Average dwell time nationallicence Time-varying delays nationallicence Lian Jie Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, 116024, Dalian, P.R. China aut Zhang Kai Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, 116024, Dalian, P.R. China aut Nonlinear Dynamics Springer Netherlands 63/3(2011-02-01), 331-343 0924-090X 63:3<331 2011 63 11071 https://doi.org/10.1007/s11071-010-9807-2 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11071-010-9807-2 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Lian Jie Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, 116024, Dalian, P.R. China aut NATIONALLICENCE 700 1- Zhang Kai Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, 116024, Dalian, P.R. China aut NATIONALLICENCE 773 0- Nonlinear Dynamics Springer Netherlands 63/3(2011-02-01), 331-343 0924-090X 63:3<331 2011 63 11071 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer