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Elements of Information Theory (Thomas M. Cover)
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- Read more: https://english.9natree.com/read/0471241954/
#Shannonentropy #Sourcecodingtheorem #Channelcapacity #KullbackLeiblerdivergence #Ratedistortiontheory #ElementsofInformationTheory
Elements of Information Theory is a rigorous textbook by Thomas M. Cover and Joy A. Thomas, published in its second edition in 2006. It develops the mathematical language used to quantify uncertainty, represent data efficiently, and establish fundamental limits on communication and inference. Rather than treating compression, noisy channels, statistical modeling, and networks as separate engineering subjects, the book shows how probability distributions and information measures connect them. Its central objects include entropy, mutual information, relative entropy, and coding rates, followed by formal theorems that specify what is achievable in idealized large block length settings. The scope extends from lossless and lossy source coding to channel capacity, hypothesis testing, feedback, and multiuser communication. Designed principally for advanced undergraduates, graduate students, and technically prepared researchers, it is not a lightweight introduction. Carefully structured derivations, end of chapter summaries, historical notes, and extensive problems make it both a reference work and a demanding course text for readers seeking the conceptual foundations beneath modern digital communication and statistical learning.
- Amazon USA Store: https://www.amazon.com/dp/0471241954?tag=9natree-20
- Amazon Worldwide Store: https://global.buys.trade/Elements-of-Information-Theory-Thomas-M-Cover.html
- Apple Books: https://books.apple.com/us/audiobook/data-governance-guide-navigating-the-seas-of/id1779466639?itsct=books_box_link&itscg=30200&ls=1&at=1001l3bAw&ct=9natree
- eBay: https://www.ebay.com/sch/i.html?_nkw=Elements+of+Information+Theory+Thomas+M+Cover+&mkcid=1&mkrid=711-53200-19255-0&siteid=0&campid=5339060787&customid=9natree&toolid=10001&mkevt=1
- Read more: https://english.9natree.com/read/0471241954/
#Shannonentropy #Sourcecodingtheorem #Channelcapacity #KullbackLeiblerdivergence #Ratedistortiontheory #ElementsofInformationTheory
Elements of Information Theory is a rigorous textbook by Thomas M. Cover and Joy A. Thomas, published in its second edition in 2006. It develops the mathematical language used to quantify uncertainty, represent data efficiently, and establish fundamental limits on communication and inference. Rather than treating compression, noisy channels, statistical modeling, and networks as separate engineering subjects, the book shows how probability distributions and information measures connect them. Its central objects include entropy, mutual information, relative entropy, and coding rates, followed by formal theorems that specify what is achievable in idealized large block length settings. The scope extends from lossless and lossy source coding to channel capacity, hypothesis testing, feedback, and multiuser communication. Designed principally for advanced undergraduates, graduate students, and technically prepared researchers, it is not a lightweight introduction. Carefully structured derivations, end of chapter summaries, historical notes, and extensive problems make it both a reference work and a demanding course text for readers seeking the conceptual foundations beneath modern digital communication and statistical learning.
