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Titlebook: Mathematics of Complexity and Dynamical Systems; Robert A. Meyers (Editor-in-Chief) Reference work 2011 Springer Science+Business Media, L

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发表于 2025-3-21 19:09:26 | 显示全部楼层 |阅读模式
书目名称Mathematics of Complexity and Dynamical Systems
编辑Robert A. Meyers (Editor-in-Chief)
视频videohttp://file.papertrans.cn/627/626930/626930.mp4
概述Provides an in-depth treatment of the study of mathematical complexity and dynamical systems.Presents theory, techniques and applications.Demonstrates how the behavior of an entire system is often mor
图书封面Titlebook: Mathematics of Complexity and Dynamical Systems;  Robert A. Meyers (Editor-in-Chief) Reference work 2011 Springer Science+Business Media, L
描述Mathematics of Complexity and Dynamical Systems is an authoritative reference to the basic tools and concepts of complexity, systems theory, and dynamical systems from the perspective of pure and applied mathematics.  Complex systems are systems that comprise many interacting parts with the ability to generate a new quality of collective behavior through self-organization, e.g. the spontaneous formation of temporal, spatial or functional structures.  These systems are often characterized by extreme sensitivity to initial conditions as well as emergent behavior that are not readily predictable or even completely deterministic. .The more than 100 entries in this wide-ranging, single source work provide a comprehensive explication of the theory and applications of mathematical complexity, covering ergodic theory, fractals and multifractals, dynamical systems, perturbation theory, solitons, systems and control theory, and related topics.  Mathematics of Complexity and Dynamical Systems is an essential reference for all those interested in mathematical complexity, from undergraduate and graduate students up through professional researchers.
出版日期Reference work 2011
关键词Dynamical Systems; Dynamical systems book; Ergodic Theory; Fractals and Multifractals; Mathematical Comp
版次1
doihttps://doi.org/10.1007/978-1-4614-1806-1
isbn_ebook978-1-4614-1806-1
copyrightSpringer Science+Business Media, LLC 2011
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Igor M. Sokolovrm. However, in this case the model predictive control problem is considered with some enhancements including, for example, a connection matrix defining the pattern of control moves allowed in the prediction horizon. The generalized predictive controller is first considered for the plant without the
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George Osipenkom considered is the nonlinear minimum variance filtering problem. However, there is also an introduction to other linear and nonlinear estimation problems. The Kalman filter was used in many of the control solutions considered earlier and this is described in more detail. The algorithm for the compu
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