%0 Journal Article
%T Improved delay-dependent globally asymptotic stability of delayed uncertain recurrent neural networks with Markovian jumping parameters<br>
%A Ji Yan
%A Cui Bao-Tong
%A <br>
%J 中国物理 B
%D 2010
%I 
%X In this paper, we have improved delay-dependent stability criteria for recurrent neural networks with a delay varying over a range and Markovian jumping parameters. The criteria improve over some previous ones in that they have fewer matrix variables yet less conservatism. In addition, a numerical example is provided to illustrate the applicability of the result using the linear matrix inequality toolbox in MATLAB.
%K recurrent neural networks
%K time-varying delays
%K linear matrix inequality
%K Lyapunov--Krasovskii functional
%K Markovian jumping parameters<br>
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=6E709DC38FA1D09A4B578DD0906875B5B44D4D294832BB8E&cid=47EA7CFDDEBB28E0&jid=CD8D6A6897B9334F09D8D1648C376FB4&aid=8E4E844EC225E7F4C082BC746AC5978B&yid=140ECF96957D60B2&vid=2A8D03AD8076A2E3&iid=B31275AF3241DB2D&journal_id=1009-1963&journal_name=中国物理&referenced_num=0&reference_num=20