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Titlebook: Marginal and Functional Quantization of Stochastic Processes; Harald Luschgy,Gilles Pagès Book 2023 The Editor(s) (if applicable) and The

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书目名称Marginal and Functional Quantization of Stochastic Processes
编辑Harald Luschgy,Gilles Pagès
视频video
概述State of the art monograph on the quantization of stochastic processes.Contains applications to numerical probability and mathematical finance.Presents deep connections between optimal quantization an
丛书名称Probability Theory and Stochastic Modelling
图书封面Titlebook: Marginal and Functional Quantization of Stochastic Processes;  Harald Luschgy,Gilles Pagès Book 2023 The Editor(s) (if applicable) and The
描述.Vector Quantization, a pioneering discretization method based on nearest neighbor search, emerged in the 1950s primarily in signal processing, electrical engineering, and information theory. Later in the 1960s, it evolved into an automatic classification technique for generating prototypes of extensive datasets. In modern terms, it can be recognized as a seminal contribution to unsupervised learning through the k-means clustering algorithm in data science...In contrast, Functional Quantization, a more recent area of study dating back to the early 2000s, focuses on the quantization of continuous-time stochastic processes viewed as random vectors in Banach function spaces. This book distinguishes itself by delving into the quantization of random vectors with values in a Banach space—a unique feature of its content. ..Its main objectives are twofold: first, to offer a comprehensive and cohesive overview of the latest developments as well as several new results in optimal quantization theory, spanning both finite and infinite dimensions, building upon the advancements detailed in Graf and Luschgy‘s Lecture Notes volume. Secondly, it serves to demonstrate how optimal quantization can b
出版日期Book 2023
关键词Vector Quantization; Continuous time stochastic processus; Signal transmission; Cluster algorithms; Spac
版次1
doihttps://doi.org/10.1007/978-3-031-45464-6
isbn_softcover978-3-031-45466-0
isbn_ebook978-3-031-45464-6Series ISSN 2199-3130 Series E-ISSN 2199-3149
issn_series 2199-3130
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Functional Quantization, Small Ball Probabilities, Metric Entropy and Series Expansions for Gaussiann errors. A first approach to the construction of good quantizations (scalar product quantizations), being close to rate optimality and having a general distortion mismatch feature, is based on series expansions.
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Optimal Quantization From the Numerical Side (Static)sion. A final general remark is that the quadratic versions of these stochastic algorithms (? = 2) are usually more stable. It is also in this quadratic setting that most theoretical results have been obtained.
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s highlight recent developments in lymphocyte development, Ig gene rearrangements and somatic hypermutation, chromatin structure modification, B lymphocyte signaling and fate, receptor editing, and autoimmunity. .978-1-4419-4283-8978-0-387-46530-2Series ISSN 0065-2598 Series E-ISSN 2214-8019
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