<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">ZHENGWEI CHEN</style></author><author><style face="normal" font="default" size="100%">RUOJUN ZHANG</style></author><author><style face="normal" font="default" size="100%">LINSHAN WANG</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">FINITE-TIME STOCHASTIC SYNCHRONIZATION FOR A CLASS OF BAM NEURAL NETWORKS WITH UNCERTAIN PARAMETERS</style></title><secondary-title><style face="normal" font="default" size="100%">Communications in Applied Analysis</style></secondary-title><short-title><style face="normal" font="default" size="100%">STOCHASTIC SYNCHRONIZATION FOR BAMNN </style></short-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">74H65</style></keyword><keyword><style  face="normal" font="default" size="100%">93E35</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">06/2016</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.acadsol.eu/en/articles/20/2/7.pdf</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">20</style></volume><pages><style face="normal" font="default" size="100%">14</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p class=&quot;rtejustify&quot;&gt;This paper is concerned with the finite-time stochastic synchronization for a class of bidirectional associative memory (BAM) neural networks with uncertain parameters. With the adaptive control method, sufficient conditions for finite-time stochastic synchronization and parameters identification are derived based on finite-time stability theory of stochastic differential equations. We also provide a numerical example to support the effectiveness of the proposed method.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><work-type><style face="normal" font="default" size="100%">scientific: mathematics</style></work-type><section><style face="normal" font="default" size="100%">263</style></section></record></records></xml>