5 edition of **Topics in statistical information theory** found in the catalog.

Topics in statistical information theory

Solomon Kullback

- 334 Want to read
- 13 Currently reading

Published
**1987**
by Springer-Verlag in Berlin, New York
.

Written in English

- Stochastic processes.,
- Information theory.,
- Mathematical statistics.

**Edition Notes**

Statement | S. Kullback, J.C. Keegel, J.H. Kullback. |

Series | Lecture notes in statistics ;, 42, Lecture notes in statistics (Springer-Verlag) ;, v. 42. |

Contributions | Keegel, J. C., Kullback, J. H. |

Classifications | |
---|---|

LC Classifications | QA274 .K85 1987 |

The Physical Object | |

Pagination | ix, 158 p. ; |

Number of Pages | 158 |

ID Numbers | |

Open Library | OL2084366M |

ISBN 10 | 0387965122 |

LC Control Number | 88123671 |

Book Abstract: This IEEE Classic Reissue provides at an advanced level, a uniquely fundamental exposition of the applications of Statistical Communication Theory to a vast spectrum of important physical problems. Included are general analysis of signal detection, estimation, measurement, and related topics involving information transfer. This is definitely not my thing, but I thought I would mention a video I watched three times and will watch again to put it firmly in my mind. It described how the living cell works with very good animations presented. Toward the end of the vide.

Developed by Claude Shannon and Norbert Wiener in the late s, information theory, or statistical communication theory, deals with the theoretical underpinnings of a wide range of communication devices: radio, television, radar, computers, telegraphy, and more. This book is an excellent introduction to the mathematics underlying the theory. statistical method advanced, is the question of what every PhD student should tles used in our profession to refer to various topics, with theory comprising many topics that can proﬁtably be considered without motivating examples or the existence of even hypothetical problems, and methods comprising many.

Information Theory deals with a basic challenge in communication: How do we transmit information efficiently? In addressing that issue, Information Theorists have created a rich mathematical framework to describe communication processes with tools to characterize so-called fundamental limits of data compression and transmission. Highly useful text studies the logarithmic measures of information and their application to testing statistical hypotheses. Topics include introduction and definition of measures of information, their relationship to Fisher's information measure and sufficiency, fundamental inequalities of information theory, much more.

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The relevance of information theory to statistical theory and its applications to stochastic processes is a unifying influence in these TOPICS. The integral representation of discrimination information is presented in these TOPICS reviewing various approaches used in the literature, and is also.

The relevance of information theory to statistical theory and its applications to stochastic processes is a unifying influence in these TOPICS.

The integral representation of discrimination information is presented in these TOPICS reviewing various approaches used in the literature, and is also developed herein using intrinsically information Cited by: Quantum Information Theory brings together ideas from Classical Information Theory, Quantum Mechanics and Computer Science.

Theorems and techniques of various branches of Mathematics and Mathematical Physics, in particular Group Theory, Probability Theory and Quantum Statistical Physics find applications in this fascinating and fast–growing.

Note: Citations are based on reference standards. However, formatting rules can vary widely between applications and fields of interest or study. The specific requirements or preferences of your reviewing publisher, classroom teacher, institution or organization should be applied.

The relevance of information theory to statistical theory and its applications to stochastic processes is a unifying influence in these TOPICS.

The integral representation of discrimination informatio. Get this from a library. Topics in statistical information theory. [Solomon Kullback; J C Keegel; J H Kullback] -- The relevance of information theory to statistical theory and its applications to stochastic processes is a unifying influence in these TOPICS.

The integral representation of discrimination. Developed by Claude Shannon and Norbert Wiener in the late s, information theory, or statistical communication theory, deals with the theoretical underpinnings of a wide range of communication devices: radio, television, radar, computers, telegraphy, and more.

This book is an excellent introduction to the mathematics underlying the chickashacf.com by: Chapter 8, there is Chapter 0 on “statistical mathematics” (that is, mathe-matics with strong relevance to statistical theory) that provides much of the general mathematical background for probability and statistics.

The mathe-matics in this chapter is prerequisite for the main part of the book, and it. Applications of fundamental topics of information theory include lossless data compression (e.g. ZIP files), lossy data compression (e.g. MP3s and JPEGs), and channel coding (e.g.

for DSL). Information theory is used in information retrieval, intelligence gathering, gambling, statistics, and even in.

This volume is a reorganized edition of Kei Takeuchi’s works on various problems in mathematical statistics based on papers and monographs written since the s on several topics in mathematical statistics and published in various journals in English and in chickashacf.com: Springer Japan.

LISREL – proprietary statistical software package List of basic statistics topics – redirects to Outline of statistics List of convolutions of probability distributions.

There are many books on information theory, but what makes this book unique (and in my opinion what makes it so outstanding) is the way it integrates information theory with statistical inference.

The book covers topics including coding theory, Bayesian inference, and neural networks, but it treats them all as different pieces of a unified. Theory and Methods of Statistics covers essential topics for advanced graduate students and professional research statisticians.

This comprehensive resource covers many important areas in one manageable volume, including core subjects such as probability theory, mathematical statistics, and linear models, and various special topics, including. Before we delve into the details of the statistical theory of estimation and hypothesis testing, we will present a simple example which will serve to illustrate several aspects of the theory.

An Introductory Example I have a hot{air popcorn popper which I have been using a lot lately. It is a. Feb 01, · The last few years have witnessed rapid advancements in information and coding theory research and applications.

This book provides a comprehensive guide to selected topics, both ongoing and emerging, in information and coding theory. Information theory is a branch of the mathematical theory of probability and mathematical statistics with wide applications in a variety of fields. This book studies the logarithmic measures of information and their application to testing statistical hypotheses.

Jun 14, · Developed by Claude Shannon and Norbert Wiener in the late s, information theory, or statistical communication theory, deals with the theoretical underpinnings of a wide range of communication devices: radio, television, radar, computers, telegraphy, and more.

This book is an excellent introduction to the mathematics underlying the theory. Apr 25, · First published by Wiley inthis book is being re-issued with a new Preface by the author. The roots of the book lie in the writings of RA Fisher both as concerns results and the general stance to statistical science, and this stance was the determining factor in the author's selection of topics.

Apr 27, · An Elementary Introduction to Statistical Learning Theory is an excellent book for courses on statistical learning theory, pattern recognition, and machine learning at the upper-undergraduate and graduate levels. It also serves as an introductory reference for researchers and practitioners in the fields of engineering, computer science.

Information Theory Lecture Notes. This is a graduate-level introduction to mathematics of information theory. This note will cover both classical and modern topics, including information entropy, lossless data compression, binary hypothesis testing, channel coding, and lossy data compression.

relying on single-shot results, Feinstein’s lemma and information spectrum methods. We have added a number of technical re nements and new topics, which correspond to our own interests (e.g., modern aspects of nite blocklength results and applications of information theoretic methods to statistical decision theory and combinatorics).Dec 28, · A lot of people recommend, The Elements of Statistical Learning, but I don’t.

I’m really not a fan of that book. The authors start each chapter with a brief introduction to the topic at hand, and then often push many technically complicated method.Highly useful text studies the logarithmic measures of information and their application to testing statistical hypotheses.

Topics include introduction and definition of measures of information, their relationship to Fisher's information measure and sufficiency, fundamental inequalities of information theory, much more/5(15).