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Titlebook: Mathematical Modeling of Collective Behavior in Socio-Economic and Life Sciences; Giovanni Naldi,Lorenzo Pareschi,Giuseppe Toscani Book 20

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书目名称Mathematical Modeling of Collective Behavior in Socio-Economic and Life Sciences
编辑Giovanni Naldi,Lorenzo Pareschi,Giuseppe Toscani
视频video
概述A comprehensive and concise presentation of current research from experts in various disciplines compiled in one volume.Applications to a variety of disciplines including finance, social science, and
丛书名称Modeling and Simulation in Science, Engineering and Technology
图书封面Titlebook: Mathematical Modeling of Collective Behavior in Socio-Economic and Life Sciences;  Giovanni Naldi,Lorenzo Pareschi,Giuseppe Toscani Book 20
描述Mathematical modeling using dynamical systems and partial differential equations is now playing an increasing role in the understanding of complex multi-scale phenomena. Behavior in seemingly different areas such as sociology, economics, and the life sciences can be described by closely related models.Using examples from financial markets and modern warfare to the flocking of birds and the swarming of bacteria, the collected research in this volume demonstrates the common methodological approaches and tools for modeling and simulating collective behavior.The topics presented point toward new and challenging frontiers of applied mathematics, making the volume a useful reference text for applied mathematicians, physicists, biologists, and economists involved in the modeling of socio-economic systems.
出版日期Book 2010
关键词STATISTICA; collective behavior; kinetic modeling; mathematics; multi-scale modeling; nonlinear analysis;
版次1
doihttps://doi.org/10.1007/978-0-8176-4946-3
isbn_ebook978-0-8176-4946-3Series ISSN 2164-3679 Series E-ISSN 2164-3725
issn_series 2164-3679
copyrightSpringer Science+Business Media, LLC 2010
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to separate the multichannel spatial filtering operation from a single-channel filterbank which computes a frequency decomposition. We also introduce an adaptive variant, which updates the spatial filter coefficients at each time frame based on the previous inputs. Finally, we demonstrate that thes
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Anirban Chakraborti,Guido Germanoic models to such variation, robust features have traditionally been used to create an invariant representation of the acoustic space. Most commonly, robust feature-extraction strategies have explored three principal areas: (a) enhancing the speech signal, with a goal of improving the perceptual qua
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supposition results in a logic called . by Quine. or . by some free logicians. The main concern of free logic was and is therefore existential presuppositions with respect to singular terms. In standard systems of QL= we usually have for every singular term . and every variable v the theorem 3∃(v =
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