information theory and reliable communication pdf

Information Theory And Reliable Communication Pdf

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Information theory

Due to the COVID crisis, the information below is subject to change, in particular that concerning the teaching mode presential, distance or in a comodal or hybrid format. Teacher s. Information representation: decorrelation coding and entropic coding. Information security: cryptographic coding. Information correction: channel coding theory and error-correcting codes.

Information theory is the scientific study of the quantification , storage , and communication of information. The field was fundamentally established by the works of Harry Nyquist and Ralph Hartley , in the s, and Claude Shannon in the s. The field is at the intersection of probability theory , statistics , computer science, statistical mechanics , information engineering , and electrical engineering. A key measure in information theory is entropy. Entropy quantifies the amount of uncertainty involved in the value of a random variable or the outcome of a random process. For example, identifying the outcome of a fair coin flip with two equally likely outcomes provides less information lower entropy than specifying the outcome from a roll of a die with six equally likely outcomes. Some other important measures in information theory are mutual information , channel capacity, error exponents , and relative entropy.

Information Theory And Reliable Communication Gallager Pdf Free Download

All rights reserved. Reproduction or translation of any part of this work beyond that permitted by Sections or of the United States Copyright Act without the permission of the copyright owner is unlawful. This book is designed primarily for use as a first-year graduate text in information theory, suitable for both engineers and mathematicians. It is assumed that the reader has some understanding of freshman calculus and elementary probability, and in the later chapters some introductory random process theory. Unfortunately there is one more requirement that is harder to meet. The reader must have a reasonable level of mathematical maturity and capability for abstract thought.

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Information theory and coding

Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. DOI: Gallager Published Mathematics. Communication Systems and Information Theory.

Course Pre-requisites: EE and familiarity with basic concepts of probability. Course Outline: This course will serve as the first among the sequence of two courses in the area of Information Theory. The first part of the first course will introduce the ideal of uncertainty, which is a useful measure in studying the data compression and deriving the results related to compression.

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