
Author 
JV Stone 
ISBN10 
9780956372857 
Year 
2015 
Pages 
260 
Language 
en 
Publisher 
Sebtel Press 
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Originally developed by Claude Shannon in the 1940s, information theory laid the foundations for the digital revolution, and is now an essential tool in telecommunications, genetics, linguistics, brain sciences, and deep space communication. In this richly illustrated book, accessible examples are used to introduce information theory in terms of everyday games like ‘20 questions’ before more advanced topics are explored. Online MatLab and Python computer programs provide handson experience of information theory in action, and PowerPoint slides give support for teaching. Written in an informal style, with a comprehensive glossary and tutorial appendices, this text is an ideal primer for novices who wish to learn the essential principles and applications of information theory.

Author 
James V.. Stone 
ISBN10 
0956372856 
Year 
2015 
Pages 
243 
Language 
en 
Publisher 
Tutorial Introductions 
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Originally developed by Claude Shannon in the 1940s, the theory of information laid the foundations for the digital revolution, and is now an essential tool in deep space communication, genetics, linguistics, data compression, and brain sciences. In this richly illustrated book, accessible examples are used to show how information theory can be understood in terms of everyday games like '20 Questions', and the simple MatLab programs provided give handson experience of information theory in action. Written in a tutorial style, with a comprehensive glossary, this text represents an ideal primer for novices who wish to become familiar with the basic principles of information theory.

Author 
James V. Stone 
ISBN10 
9780956372840 
Year 
20130601 
Pages 
170 
Language 
en 
Publisher 
Sebtel Press 
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In this richly illustrated book, a range of accessible examples are used to show how Bayes' rule is actually a natural consequence of commonsense reasoning. The tutorial style of writing, combined with a comprehensive glossary, makes this an ideal primer for the novice who wishes to become familiar with the basic principles of Bayesian analysis.

Author 
James V. Stone 
ISBN10 
0262693151 
Year 
2004 
Pages 
193 
Language 
en 
Publisher 
MIT Press 
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A tutorialstyle introduction to a class of methods for extracting independent signals from a mixture of signals originating from different physical sources; includes MatLab computer code examples.

Author 
Imre Csiszár 
ISBN10 
1933019050 
Year 
2004 
Pages 
115 
Language 
en 
Publisher 
Now Publishers Inc 
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Information Theory and Statistics: A Tutorial is concerned with applications of information theory concepts in statistics, in the finite alphabet setting. The topics covered include large deviations, hypothesis testing, maximum likelihood estimation in exponential families, analysis of contingency tables, and iterative algorithms with an "information geometry" background. Also, an introduction is provided to the theory of universal coding, and to statistical inference via the minimum description length principle motivated by that theory. The tutorial does not assume the reader has an indepth knowledge of Information Theory or statistics. As such, Information Theory and Statistics: A Tutorial, is an excellent introductory text to this highlyimportant topic in mathematics, computer science and electrical engineering. It provides both students and researchers with an invaluable resource to quickly get up to speed in the field.

Author 
David J. C. MacKay 
ISBN10 
0521642981 
Year 
20030925 
Pages 
628 
Language 
en 
Publisher 
Cambridge University Press 
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Fun and exciting textbook on the mathematics underpinning the most dynamic areas of modern science and engineering.

Author 
John Robinson Pierce 
ISBN10 
0486240614 
Year 
1961 
Pages 
305 
Language 
en 
Publisher 
Courier Corporation 
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Behind the familiar surfaces of the telephone, radio, and television lies a sophisticated and intriguing body of knowledge known as information theory. This is the theory that has permeated the rapid development of all sorts of communication, from color television to the clear transmission of photographs from the vicinity of Jupiter. Even more revolutionary progress is expected in the future. To give a solid introduction to this burgeoning field, J. R. Pierce has revised his wellreceived 1961 study of information theory for an uptodate second edition. Beginning with the origins of the field, Dr. Pierce follows the brilliant formulations of Claude Shannon and describes such aspects of the subject as encoding and binary digits, entropy. language and meaning, efficient encoding , and the noisy channel. He then goes beyond the strict confines of the topic to explore the ways in which information theory relates to physics, cybernetics, psychology, and art. Mathematical formulas are introduced at the appropriate points for the benefit of serious students. A glossary of terms and an appendix on mathematical notation are provided to help the less mathematically sophisticated. J. R. Pierce worked for many years at the Bell Telephone Laboratories, where he became Director of Research in Communications Principles. He is currently affiliated with the engineering department of the California Institute of Technology. While his background is impeccable, Dr. Pierce also possesses an engaging writing style that makes his book all the more welcome. An Introduction to Information Theory continues to be the most impressive nontechnical account available and a fascinating introduction to the subject for laymen. "An uncommonly good study. . . . Pierce's volume presents the most satisfying discussion to be found."? Scientific American.

Author 
Dr. James V. Stone 
ISBN10 
0993367933 
Year 
20161015 
Pages 
188 
Language 
en 
Publisher 

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Discovered by an 18th century mathematician and preacher, Bayes' rule is a cornerstone of modern probability theory. In this richly illustrated book, a range of accessible examples is used to show how Bayes' rule is actually a natural consequence of common sense reasoning. Bayes' rule is then derived using intuitive graphical representations of probability, and Bayesian analysis is applied to parameter estimation. The tutorial style of writing, combined with a comprehensive glossary, makes this an ideal primer for novices who wish to become familiar with the basic principles of Bayesian analysis. Note that this book includes Python (3.0) code snippets, which reproduce key numerical results and diagrams.

Author 
Solomon Kullback 
ISBN10 
9780486142043 
Year 
20120911 
Pages 
416 
Language 
en 
Publisher 
Courier Corporation 
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Highly useful text studies logarithmic measures of information and their application to testing statistical hypotheses. Includes numerous worked examples and problems. References. Glossary. Appendix. 1968 2nd, revised edition.

Author 
Robert Gallager 
ISBN10 
9783709129456 
Year 
20140504 
Pages 
115 
Language 
en 
Publisher 
Springer 
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Author 
Ivan B. Djordjevic 
ISBN10 
9783319228167 
Year 
20151005 
Pages 
269 
Language 
en 
Publisher 
Springer 
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This book is a selfcontained, tutorialbased introduction to quantum information theory and quantum biology. It serves as a singlesource reference to the topic for researchers in bioengineering, communications engineering, electrical engineering, applied mathematics, biology, computer science, and physics. The book provides all the essential principles of the quantum biological information theory required to describe the quantum information transfer from DNA to proteins, the sources of genetic noise and genetic errors as well as their effects. Integrates quantum information and quantum biology concepts; Assumes only knowledge of basic concepts of vector algebra at undergraduate level; Provides a thorough introduction to basic concepts of quantum information processing, quantum information theory, and quantum biology; Includes indepth discussion of the quantum biological channel modelling, quantum biological channel capacity calculation, quantum models of aging, quantum models of evolution, quantum models on tumor and cancer development, quantum modeling of bird navigation compass, quantum aspects of photosynthesis, quantum biological error correction.
Discovered by an 18th century mathematician and preacher, Bayes' rule is a cornerstone of modern probability theory. In this richly illustrated book, a range of accessible examples is used to show how Bayes' rule is actually a natural consequence of common sense reasoning. Bayes' rule is then derived using intuitive graphical representations of probability, and Bayesian analysis is applied to parameter estimation using the MatLab and Python programs provided online. The tutorial style of writing, combined with a comprehensive glossary, makes this an ideal primer for novices who wish to become familiar with the basic principles of Bayesian analysis. Note that this MatLab version of Bayes' Rule includes working MatLab code snippets alongside the relevant equations.

Author 
Raymond W. Yeung 
ISBN10 
9781441986085 
Year 
20121206 
Pages 
412 
Language 
en 
Publisher 
Springer Science & Business Media 
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This book provides an uptodate introduction to information theory. In addition to the classical topics discussed, it provides the first comprehensive treatment of the theory of IMeasure, network coding theory, Shannon and nonShannon type information inequalities, and a relation between entropy and group theory. ITIP, a software package for proving information inequalities, is also included. With a large number of examples, illustrations, and original problems, this book is excellent as a textbook or reference book for a senior or graduate level course on the subject, as well as a reference for researchers in related fields.

Author 
Lajos Diosi 
ISBN10 
9783642161179 
Year 
20110602 
Pages 
161 
Language 
en 
Publisher 
Springer 
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This short and concise primer takes the vantage point of theoretical physics and the unity of physics. It sets out to strip the burgeoning field of quantum information science to its basics by linking it to universal concepts in physics. An extensive lecture rather than a comprehensive textbook, this volume is based on courses delivered over several years to advanced undergraduate and beginning graduate students, but essentially it addresses anyone with a working knowledge of basic quantum physics. Readers will find these lectures a most adequate entry point for theoretical studies in this field. For the second edition, the authors has succeeded in adding many new topics while sticking to the conciseness of the overall approach. A new chapter on qubit thermodynamics has been added, while new sections and subsections have been incorporated in various chapter to deal with weak and timecontinuous measurements, periodfinding quantum algorithms and quantum error corrections. From the reviews of the first edition: "The best things about this book are its brevity and clarity. In around 100 pages it provides a tutorial introduction to quantum information theory, including problems and solutions. ... it’s worth a look if you want to quickly get up to speed with the language and central concepts of quantum information theory, including the background classical information theory." (Craig Savage, Australian Physics, Vol. 44 (2), 2007)

Author 
Thomas M. Cover 
ISBN10 
9781118585771 
Year 
20121128 
Pages 
792 
Language 
en 
Publisher 
John Wiley & Sons 
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The latest edition of this classic is updated with new problem sets and material The Second Edition of this fundamental textbook maintains the book's tradition of clear, thoughtprovoking instruction. Readers are provided once again with an instructive mix of mathematics, physics, statistics, and information theory. All the essential topics in information theory are covered in detail, including entropy, data compression, channel capacity, rate distortion, network information theory, and hypothesis testing. The authors provide readers with a solid understanding of the underlying theory and applications. Problem sets and a telegraphic summary at the end of each chapter further assist readers. The historical notes that follow each chapter recap the main points. The Second Edition features: * Chapters reorganized to improve teaching * 200 new problems * New material on source coding, portfolio theory, and feedback capacity * Updated references Now current and enhanced, the Second Edition of Elements of Information Theory remains the ideal textbook for upperlevel undergraduate and graduate courses in electrical engineering, statistics, and telecommunications. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.