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Information theory and selected appl...

Ben-Naim, Arieh.

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Information theory and selected applications

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Information theory and selected applications/ by Arieh Ben-Naim.
作者:	Ben-Naim, Arieh.
出版者:	Cham :Springer International Publishing : : 2023.,
面頁冊數:	xv, 232 p. :ill. (some col.), digital ;24 cm.
內容註:	Introduction and Caveats -- Intermolecular interactions, correlations, and Mutual Information -- Application of Multivariate Mutual Information to study spin systems -- Entropy of Mixing and Entropy of Assimilation, an Informational Theoretical Approach -- Information transmission between molecules in binding systems -- Calculations of the "best-guess" probability distribution using Shannon's Measure of Information.
Contained By:	Springer Nature eBook
標題:	Information theory. -
電子資源:	https://doi.org/10.1007/978-3-031-21276-5
ISBN:	9783031212765

Information theory and selected applications
Ben-Naim, Arieh.

Information theory and selected applications[electronic resource] /by Arieh Ben-Naim. - Cham :Springer International Publishing :2023. - xv, 232 p. :ill. (some col.), digital ;24 cm.

Introduction and Caveats -- Intermolecular interactions, correlations, and Mutual Information -- Application of Multivariate Mutual Information to study spin systems -- Entropy of Mixing and Entropy of Assimilation, an Informational Theoretical Approach -- Information transmission between molecules in binding systems -- Calculations of the "best-guess" probability distribution using Shannon's Measure of Information.

This book focuses on analysing the applications of the Shannon Measure of Information (SMI) The book introduces the concept of frustration and discusses the question of the quantification of this concept within information theory (IT), while it also focuses on the interpretation of the entropy of systems of interacting particles in terms of the SMI and of mutual information. The author examines the question of the possibility of measuring the extent of frustration using mutual information and discusses some classical examples of processes of mixing and assimilation for which the entropy changes are interpreted in terms of SMI. A description of a few binding systems and the interpretation of cooperativity phenomena in terms of mutual information are also presented, along with a detailed discussion on the general method of using maximum SMI in order to find the "best-guess" probability distribution. This book is a valuable contribution to the field of information theory and will be of great interest to any scientist who is interested in IT and in its potential applications.

ISBN: 9783031212765

Standard No.: 10.1007/978-3-031-21276-5doiSubjects--Topical Terms:

542527
Information theory.

LC Class. No.: Q360 / .B45 2023

Dewey Class. No.: 003.54

Information theory and selected applications
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505 0 $a Introduction and Caveats -- Intermolecular interactions, correlations, and Mutual Information -- Application of Multivariate Mutual Information to study spin systems -- Entropy of Mixing and Entropy of Assimilation, an Informational Theoretical Approach -- Information transmission between molecules in binding systems -- Calculations of the "best-guess" probability distribution using Shannon's Measure of Information.
520 $a This book focuses on analysing the applications of the Shannon Measure of Information (SMI) The book introduces the concept of frustration and discusses the question of the quantification of this concept within information theory (IT), while it also focuses on the interpretation of the entropy of systems of interacting particles in terms of the SMI and of mutual information. The author examines the question of the possibility of measuring the extent of frustration using mutual information and discusses some classical examples of processes of mixing and assimilation for which the entropy changes are interpreted in terms of SMI. A description of a few binding systems and the interpretation of cooperativity phenomena in terms of mutual information are also presented, along with a detailed discussion on the general method of using maximum SMI in order to find the "best-guess" probability distribution. This book is a valuable contribution to the field of information theory and will be of great interest to any scientist who is interested in IT and in its potential applications.
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