Information is the source of a communication system, whether it is analog or digital. Information theory is a mathematical approach to the study of coding of information along with the quantification, storage, and communication of information. Conditions of Occurrence of Events If we consider an event, there are three conditions of occurrence. If the event has not occurred, there is a condition of uncertainty.
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Information and Coding by Karl Petersen - AMS , The aim is to review the many facets of information, coding, and cryptography, including their uses throughout history and their mathematical underpinnings. Prerequisites included high-school mathematics and willingness to deal with unfamiliar ideas. The applications included demonstrate the importance of these codes in a wide range of everyday technologies.
This text covers the basic notions of algorithmic information theory: Kolmogorov complexity, Solomonoff universal a priori probability, effective Hausdorff dimension, etc.
This survey will motivate readers to explore the emerging domain of Science of Information. The basic idea is to introduce redundancy so that the original information can be recovered Prior programming ability and some math skills will be needed.
This book is intended to be self contained. The focus will be on neuroscientific topics. In this book, we describe the decompressor first. We study quantum mechanics for quantum information theory, we give important unit protocols of teleportation, super-dense coding, etc. Gray - Information Systems Laboratory , The conditional rate-distortion function has proved useful in source coding problems involving the possession of side information.
This book represents an early work on conditional rate distortion functions and related theory. Gruenwald, Paul M. Vitanyi - CWI , We introduce algorithmic information theory, also known as the theory of Kolmogorov complexity.
Chaitin - Springer , The final version of a course on algorithmic information theory and the epistemology of mathematics. The book discusses the nature of mathematics in the light of information theory, and sustains the thesis that mathematics is quasi-empirical. It is not surprising that physics and the theory of information are inherently connected. Quantum information theory is a research area whose goal is to explore this connection.
We will begin with basic principles and methods for reasoning about quantum information, and then move on to a discussion of various results concerning quantum information. The course is aimed at EE graduate students in the area of Communications and Information Theory, or graduate students in Physics. Schumann - arXiv , A short review of ideas in quantum information theory.
Quantum mechanics is presented together with some useful tools for quantum mechanics of open systems. The treatment is pedagogical and suitable for beginning graduates in the field. These notes provide a broad coverage of key results, techniques, and open problems in network information theory.
Chaitin - World Scientific , In this mathematical autobiography, Gregory Chaitin presents a technical survey of his work and a non-technical discussion of its significance. The technical survey contains many new results, including a detailed discussion of LISP program size. MacKay - University of Cambridge , This text discusses the theorems of Claude Shannon, starting from the source coding theorem, and culminating in the noisy channel coding theorem.
Along the way we will study simple examples of codes for data compression and error correction. Gray - Springer , The book covers the theory of probabilistic information measures and application to coding theorems for information sources and noisy channels. This is an up-to-date treatment of traditional information theory emphasizing ergodic theory.
The course will study how information is measured in terms of probability and entropy, and the relationships among conditional and joint entropies; etc. It presents network coding for the transmission from a single source node, and deals with the problem under the more general circumstances when there are multiple source nodes.
The author tried to present the material in the most direct fashion possible. It laid the modern foundations for what is now coined Information Theory.
MacKay - Cambridge University Press , A textbook on information theory, Bayesian inference and learning algorithms, useful for undergraduates and postgraduates students, and as a reference for researchers.
Essential reading for students of electrical engineering and computer science.
Information & Coding Theory
Digital Communication - Information Theory