An Introduction to Kolmogorov Complexity and Its Applications 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

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Ming Li 作者

Springer

译者

2008-11-21 出版日期

792 页数

USD 84.95 价格

Hardcover

丛书系列

9780387339986 图书编码

An Introduction to Kolmogorov Complexity and Its Applications 在线电子书图书标签: Math Information_Theory 计算机数学教材复杂性 Kolmogorov_Complexity CS

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An Introduction to Kolmogorov Complexity and Its Applications 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

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An Introduction to Kolmogorov Complexity and Its Applications 在线电子书著者简介

李明，http://www.cs.uwaterloo.ca/~mli/），加拿大计算生物学（生物信息学）学会主席，现任加拿大滑铁卢大学计算机系教授。

Paul Vitanyi，（http://homepages.cwi.nl/~paulv/），荷兰阿姆斯特丹大学计算机系教授。

An Introduction to Kolmogorov Complexity and Its Applications 在线电子书图书目录

An Introduction to Kolmogorov Complexity and Its Applications 在线电子书 pdf 下载 txt下载 epub 下载 mobi 在线电子书下载

An Introduction to Kolmogorov Complexity and Its Applications 在线电子书图书描述

'The book is outstanding and admirable in many respects ...is necessary reading for all kinds of readers from undergraduate students to top authorities in the field' - "Journal of Symbolic Logic". Written by two experts in the field, this is the only comprehensive and unified treatment of the central ideas and applications of Kolmogorov complexity. The book presents a thorough treatment of the subject with a wide range of illustrative applications. Such applications include the randomness of finite objects or infinite sequences, Martin-Loef tests for randomness, information theory, computational learning theory, the complexity of algorithms, and the thermodynamics of computing. It will be ideal for advanced undergraduate students, graduate students, and researchers in computer science, mathematics, cognitive sciences, philosophy, artificial intelligence, statistics, and physics. The book is self-contained in that it contains the basic requirements from mathematics and computer science. Included are also numerous problem sets, comments, source references, and hints to solutions of problems. New topics in this edition include Omega numbers, Kolmogorov-Loveland randomness, universal learning, communication complexity, Kolmogorov's random graphs, time-limited universal distribution, Shannon information and others.

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