学术报告

发布时间:2017年10月09日 作者:唐颖   消息来源:业务办    阅读次数:[]

报告题目D Dynamic behaviour Analysis of Delayed Recurrent Neural Networks 报告人:张先明博士(澳大利亚Swinburne University) 时间:2017年10月12日(星期四)下午,4:30 地点:数学与统计学院1楼小会议室146 Abstract: From the system engineering perspective, a neural network behaves as “a nonlinear black box”, which can model and describe nonlinear dynamics effectively. Due to such a conspicuous feature, neural networks have found a wide range of applications in several areas, e.g., image processing, associate memory, optimization, and intelligent control, and so on. This talk aims to provide some preliminary knowledge about recurrent neural network models and recent developments on global asymptotic stability of delayed neural networks, including Lypunov-Krasovskii functional method, integral inequalities and reciprocally convex approaches. 简介:张先明研究员在控制领域权威期刊Automatica发表论文6篇,在IEEE Transactions 系列杂志上发表论文16篇(其中9篇长文),6篇论文进入ESI工程及计算机领域高被引论文,其中1篇论文进入ESI工程领域前0.1%高被引论文,18篇论文发表在影响因子大于5.0 的期刊上。2011年获湖南省自然科学一等奖,2013年获国家自然科学奖二等奖,2016年获IET Control Theory & Applications 最佳论文奖。



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