报告人：陈捷
报告时间：2018年1月19日（周五）上午10:00
报告地点：博习楼327会议室
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报告摘要：Adaptive networks are well-suited to performdecentralized information processing and optimization tasks and to model varioustypes of self-organized and complex behavior encountered in nature. The agentsare linked together and cooperate with each other through local interactions tosolve distributed optimization, estimation, and inference problems inreal-time. The continuous diffusion of information across the network enablesagents to adapt their performance in relation to streaming data and networkconditions. This talk will cover the stochastic learning algorithms overdistributed networks. Specifically, the talk will focus on constrained adaptivefiltering algorithms and diffusion adaptation over multitask networks.Applications to hyperspectral image processing and bioinformatics will also bediscussed.
报告人简介：陈捷，西北工业大学教授、博导，亚太信号与信息处理协会（APSIPA）“杰出讲学专家”。获西安交通大学学士、硕士学位，特鲁瓦工程技术大学工程师、博士学位。曾在法国“拉格朗日实验室”、美国密歇根大学从事研究工作。主要研究集中在自适应信号处理、分布式优化、机器学习，以及高光谱图像处理、麦克风阵列信号处理、生物信息数据分析等方面。