Information Theory & Coding - ITC Study Materials | PDF FREE DOWNLOADInformation Theory and Coding by John Daugman. Publisher : University of Cambridge Number of pages : Description : The aims of this course are to introduce the principles and applications of information theory. The course will study how information is measured in terms of probability and entropy, and the relationships among conditional and joint entropies; how these are used to calculate the capacity of a communication channel, with and without noise; coding schemes, including error correcting codes; how discrete channels and measures of information generalize to their continuous forms; etc. Home page url. Download or read it online for free here: Download link 1.
Lecture 1: Introduction to Information Theory
Information Theory & Coding
Information theory and inference, often taught separately, are here united in one entertaining textbook. These topics lie at the heart of many exciting areas of contemporary science and engineering - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics, and cryptography. This textbook introduces Information theory in tandem with applications. Information theory is taught alongside practical communication systems, such as arithmetic coding for data compression and sparse-graph codes for error-correction. A toolbox of inference techniques, including message-passing algorithms, Monte Carlo methods, and variational approximations, are developed alongside applications of these tools to clustering, convolutional codes, independent component analysis, and neural networks. The final part of the book describes the state of the art in error-correcting codes, including low-density parity-check codes, turbo codes, and digital fountain codes -- the twenty-first century standards for satellite communications, disk drives, and data broadcast.
Information theory studies the quantification , storage , and communication of information. It was originally proposed by Claude Shannon in to find fundamental limits on signal processing and communication operations such as data compression , in a landmark paper titled " A Mathematical Theory of Communication ". Its impact has been crucial to the success of the Voyager missions to deep space, the invention of the compact disc , the feasibility of mobile phones , the development of the Internet , the study of linguistics and of human perception, the understanding of black holes , and numerous other fields. The field is at the intersection of mathematics , statistics , computer science , physics , neurobiology , information engineering , and electrical engineering. The theory has also found applications in other areas, including statistical inference , natural language processing , cryptography , neurobiology ,  human vision,  the evolution  and function  of molecular codes bioinformatics , model selection in statistics,  thermal physics ,  quantum computing , linguistics , plagiarism detection ,  pattern recognition , and anomaly detection. Applications of fundamental topics of information theory include lossless data compression e.
It seems that you're in Germany. We have a dedicated site for Germany. The understanding of the theoretical matter is supported by many examples. One particular emphasis is put on the explanation of Genomic Coding. Many examples throughout the book are chosen from this particular area and several parts of the book are devoted to this exciting implication of coding.
If you own the copyright to this book and it is wrongfully on our website, we offer a simple DOWNLOAD PDF Raymond W. Yeung Information Theory and Network Coding SPIN Fundamentals of Information Theory and Coding Design .
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