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Titlebook: Control and Modeling of Complex Systems; Cybernetics in the 2 Koichi Hashimoto,Yasuaki Oishi,Yutaka Yamamoto Book 2003 Springer Science+Bus

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发表于 2025-3-21 16:12:34 | 显示全部楼层 |阅读模式
书目名称Control and Modeling of Complex Systems
副标题Cybernetics in the 2
编辑Koichi Hashimoto,Yasuaki Oishi,Yutaka Yamamoto
视频video
丛书名称Trends in Mathematics
图书封面Titlebook: Control and Modeling of Complex Systems; Cybernetics in the 2 Koichi Hashimoto,Yasuaki Oishi,Yutaka Yamamoto Book 2003 Springer Science+Bus
描述Hidenori Kimura, renowned system and control theorist, turned 60 years of age in November, 2001. To celebrate this memorable occasion, his friends, collaborators, and former students gathered from all over the world and held a symposium in his honor on November 1 and 2, 2001, at the Sanjo Conference Hall at the University of Tokyo. Reflecting his current research interests, the symposium was entitled "Cybernetics in the 21st Century: Information and Complexity in Control Theory," and it drew nearly 150 attendees. There were twenty-five lectures, on which the present volume is based. Hidenori Kimura was born on November 3, 1941, in Tokyo, just prior to the outbreak of the Second World War. It is not hard to imagine, then, that his early days, like those of so many of his contemporaries, must have been difficult. Fortunately, the war ended in 1945, and his generation found itself thoroughly occupied with the rebuilding effort and with Japan‘s uphill journey in the last half-century. He entered the University of Tokyo in 1963, received a B. S. in 1965, an M. S. in 1967, and, in 1970, a Ph. D. degree for his dissertation "A Study of Differential Games. " After obtaining his doctorate,
出版日期Book 2003
关键词Analysis; Chaos; Signal; complex systems; information; model; modeling; optimization; robot; complexity
版次1
doihttps://doi.org/10.1007/978-1-4612-0023-9
isbn_softcover978-1-4612-6577-1
isbn_ebook978-1-4612-0023-9Series ISSN 2297-0215 Series E-ISSN 2297-024X
issn_series 2297-0215
copyrightSpringer Science+Business Media New York 2003
The information of publication is updating

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https://doi.org/10.1007/978-3-658-21839-3f uniform convergence result holds, then the traditional approach of choosing the current model to minimize the error on the observed data will eventually converge to an optimal model within the specified class. More important, the reformulation of system identification as a learning theory problem
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