Information Theory by Yao Xie

An Introduction to Information Theory and Applications

By F. Bavaud, J. C. Chappelier, and J. Kohlas—This long note contains a good survey of information theory and its applications. It introduces the basic ideas of uncertainty and information, then also the more practical extensions such as optimal coding schemes, followed by the theories underlying versions of stationary processes and Markov chains. Other challenges, as the note addresses, pertain to noisy transmission environments in coding. Highlighted here are several advanced topics that follow, including, importantly, error-correcting codes and cryptography. The resource will give both a theoretical background and a practical overview of how to encode, transmit, and secure information effectively. It is a very important guide for those who seek a deep understanding of information theory and how it relates to real problems of communication and data processing.

Author(s): F Bavaud, J C Chappelier and J Kohlas

293 Pages

Lecture Notes on Information Theory by Prof. Dr. rer. nat. Rudolf Mathar

The lecture notes of Prof. Dr. rer. nat. Rudolf Mathar give a clear and very compact introduction into information theory. These notes are divided into three key parts: the basics of information theory, source coding, and information channels. The introduction treats the basic notions and definitions in information theory in a very solid way. Source coding gives methods and different techniques that are used in encoding information, while the information channels section discusses the pattern in which information is carried and noise that affects it. This resource is a good pick for students and professionals who seek structure in the principles of information theory and its applications from a respected expert in the field.

Author(s): Prof. Dr. rer. nat. Rudolf Mathar, Institute for Theoretical Information Technology Kopernikusstr, Germany

59 Pages

Lecture Notes on statistics and information Theory

This lecture note navigates through information theory, statistics and measure theory. It covers fundamental concepts such as definitions, chain rules, data processing inequalities, and divergences and extends to optimal procedures, LeCam’s and Fano’s inequalities, and operational results like entropy and source coding. It also focus on exponential families and statistical modeling, fitting procedures, and lower bounds on testing parameters, sub-Gaussian and sub-exponential random variables, martingale methods, uniformity covering topics such as Kullback-Leibler divergence, PAC-Bayes bounds, interactive data analysis, and error bounds.

Author(s): John Duchi

464 Pages

An introduction to information Theory and Entropy

Om Carter-Introduction to information theory and entropy: It goes in deep to do some basic concepts of information theory, focusing on the concept of entropy and its applications. It does so by first investigating the measure of complexity and the elementary theories of probability before introducing some key ideas in information theory. It ranges from basic issues, such as entropy theory and the Gibbs inequality, up to Shannon's communication theory but also to practical applications in many diversified fields. Other topics dealt with are Bayes Theorem, analog channels, the Maximum Entropy Principle, and applications to biology and physics. The Kullback-Leibler information measure will be discussed in trying to cast light upon quantification of information and its relations with different fields of science. This book should be ideal for the general reader interested in information theory and its immense areas of application..

Author(s): Tom Carter

139 Pages

Information Theory for Data Communications and Processing

This is a wide-ranging text by Shlomo Shamai and Abdellatif Zaidi, covering both foundational and advanced topics in information theory applied to data communications and processing. It discusses basic issues, such as information bottleneck problems, unsupervised clustering via methods of the variational information bottleneck, and rate-distortion analysis. It proceeds to get into subjects of a higher level of difficulty: non-orthogonal eMBB and URLLC radio access, robust baseband compression techniques, and amplitude-constrained MIMO channels. Efficient algorithms have been derived for multicasting, content placement in cache networks, and the fundamental limits of caching. The title will be a ready reference for researchers and practitioners interested in the theory and practice of modern communication systems, comprehensively covering recent advancement efforts and applications in information theory.

Author(s): Shlomo Shamai, Abdellatif Zaidi

296 Pages

Information Theory and Coding cam

This is a PDF document written by J.G. Daugman on the fundamentals of the theory of information and coding. Beginning with the very basic concept of probability and uncertainty, and the concept of information, it arrives at entropies and their meaning. It deals with the source coding theorems: prefix, variable-length, and fixed-length codes. It looks into several kinds of channels, their properties, noise, and channel capacity. The further topics delve into detail with continuous information, noisy channel coding theorems, Fourier series elaborated on in making matters of convergence, orthogonal representation, and useful Fourier theorems. The text also expands into aspects such as sampling and aliasing, DFT, FFT algorithms, and the quantized degrees-of-freedom in continuous signals and concludes with discussions on the Gabor-Heisenberg-Weyl uncertainty relation and Kolmogorov complexity for a general overview of some of the key principles of information theory and coding.

Author(s): J G Daugman

75 Pages