caa a22 4500 606160426 CHVBK 20210128100629.0 cr unu---uuuuu 210128e20150201xx s 000 0 eng 10.1007/s00521-014-1735-5 doi (NATIONALLICENCE)springer-10.1007/s00521-014-1735-5 Stochastic stability analysis for neural networks with mixed time-varying delays [Elektronische Daten] [Yuechao Ma, Yuqing Zheng] This paper is concerned with the problem of the stochastic stability analysis for Markovian jumping neural networks with time-varying delays and stochastic perturbation. Some criteria for the stability and robust stability of such neural networks are derived, by means of constructing suitable Lyapunov-Krasovskii functionals and a unified linear matrix inequality (LMI) approach. Note that the LMIs can be easily solved by using the Matlab LMI toolbox and no tuning of parameters is required. Finally, numerical examples are used to illustrate the effectiveness and advantage of the proposed techniques. The Natural Computing Applications Forum, 2014 Stochastic stability nationallicence Markovian jumping nationallicence Discrete time delays nationallicence Distributed time delays nationallicence Lyapunov-Krasovskii functional nationallicence Ma Yuechao College of Science, Yanshan University, Qinhuangdao, Hebei Province, China aut Zheng Yuqing College of Science, Yanshan University, Qinhuangdao, Hebei Province, China aut Neural Computing and Applications Springer London 26/2(2015-02-01), 447-455 0941-0643 26:2<447 2015 26 521 https://doi.org/10.1007/s00521-014-1735-5 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-014-1735-5 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Ma Yuechao College of Science, Yanshan University, Qinhuangdao, Hebei Province, China aut NATIONALLICENCE 700 1- Zheng Yuqing College of Science, Yanshan University, Qinhuangdao, Hebei Province, China aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/2(2015-02-01), 447-455 0941-0643 26:2<447 2015 26 521