File Name: information theory and coding kulkarni .zip
Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. DOI: A linear programming based framework is presented to derive finite blocklength converses for coding problems in information theory which is also extendable to network settings.
In the point-to-point setting, the LP based framework recovers and in fact improves on almost all well-known finite blocklength converses for lossy joint source-channel coding, lossy source coding and channel coding.
View on IEEE. Save to Library. Create Alert. Launch Research Feed. Share This Paper. Figures and Topics from this paper. Linear programming based finite blocklength converses for some network-like problems. View 1 excerpt, references background. Research Feed. View 2 excerpts, references background. View 1 excerpt, references results. A converse for lossy source coding in the finite blocklength regime.
Information 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.
Customer Care. By: Muralidhar Kulkarni , K.
This book provides a comprehensive treatment of Information Theory and Coding. It starts with mathematical prerequisites and then uncovers all major topics by way of different chapters on Information Theory, Source Coding, Communication Channels, Error Control Codes, Burst Errors, Convolution Codes and a brief chapter on Cryptography. He is also pursuing Ph. He is a gold medalist in M. Open navigation menu.
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