书目名称 | Mathematics of Information | 副标题 | Theory and Applicati | 编辑 | Stefan Schäffler | 视频video | | 概述 | Information Theory as a Mathematical Subdiscipline and Interface to Computer Science.Exact Anchoring of the Concept of Information in Probability Theory.Introduces Applications of Information Theory, | 丛书名称 | Mathematics Study Resources | 图书封面 |  | 描述 | .Starting with the Shannon-Wiener approach to mathematical information theory, allowing a mathematical "measurement" of an amount of information, the book begins by defining the terms message and information and axiomatically assigning an amount of information to a probability. The second part explores countable probability spaces, leading to the definition of Shannon entropy based on the average amount of information; three classical applications of Shannon entropy in statistical physics, mathematical statistics, and communication engineering are presented, along with an initial glimpse into the field of quantum information. The third part is dedicated to general probability spaces, focusing on the information-theoretical analysis of dynamic systems...The book builds on bachelor-level knowledge and is primarily intended for mathematicians and computer scientists, placing a strong emphasis on rigorous proofs.. | 出版日期 | Textbook 2024 | 关键词 | Differential Entropy; Dynamic Systems; Quantum Computation; Shannon Entropy; Sufficient Statistics; infor | 版次 | 1 | doi | https://doi.org/10.1007/978-3-662-69102-1 | isbn_softcover | 978-3-662-69101-4 | isbn_ebook | 978-3-662-69102-1Series ISSN 2731-3824 Series E-ISSN 2731-3832 | issn_series | 2731-3824 | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer-Verlag GmbH, DE |
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