报告题目：Minimum-Variance Fusion Estimation for Networked Systems with Censored Measurements

报告简介：In this presentation, we talk about the minimum-variance fusion estimation problem for networked systems with censored measurements. Some background knowledge is first introduced on censored measurements from the perspectives of concepts, applications and challenges. Then, some detailed discussions are given on the optimal fusion estimation issues with network constraints, system constraints and protocol constraints, and a few methodologies for handling these constraints are discussed. The topics of convergence, optimization and performance evaluation are addressed in the framework of recursive computation, and some recent results are presented. Finally, we conclude our main contributions and some future directions.

报告人：王子栋，现任英国伦敦Brunel University讲席教授，欧洲科学院院士，欧洲科学与艺术院院士，IEEE Fellow，International Journal of Systems Science主编，Neurocomputing主编。多年来从事控制理论、机器学习、生物信息学等方面研究，在SCI刊物上发表国际论文六百余篇。现任或曾任十二种国际刊物的主编、副编辑或编委。曾任旅英华人自动化及计算机协会主席、东华大学长江学者讲座教授、清华大学国家级专家。

报告时间：2023年3月1日（星期三）下午 4:00-6:00

报告地点：腾讯会议，ID：537-652-212

主办单位：扬州大学数学科学学院

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