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 |  |
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 |
doi | https://doi.org/10.1007/978-3-031-45464-6 |
isbn_softcover | 978-3-031-45466-0 |
isbn_ebook | 978-3-031-45464-6Series ISSN 2199-3130 Series E-ISSN 2199-3149 |
issn_series | 2199-3130 |
copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |