In this presentation, we talk about the state estimation problems for networked systems under unconventional measurements. Such unconventional measurements include, but are not limited to, 1) randomly occurring phenomena (e.g. delays, dropouts, saturations, quantization, fading, disorders, resolutions, biases, degradations, censorings, outliers), 2) effects induced by communication protocols (e.g. event-triggering protocol, round-robin protocol, try-once-discard protocol and random access protocol), and 3) effects induced by coding-decoding mechanisms (e.g. encryption-decryption scheme). Some background knowledge is first introduced from the perspectives of concepts, applications and challenges. Then, some detailed discussions are given on the optimal estimation issues with network constraints, system constraints and protocol constraints, and a few developed methodologies for handling unconventional measurements are discussed. Finally, we conclude our main contributions and some future directions.
主讲人：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七百余篇。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、东华大学国家级领军人才、清华大学国家级专家。