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Introduction to Information Theory and Data Compression, Second Edition
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Author: Greg A. Harris, Peter D. Johnson, Darrel R. Hankerson
List Price: $89.95
Our Price: Click to see the latest and low price
ISBN: 1584883138
Publisher: Chapman & Hall (February, 2003)
Edition: Hardcover
Sales Rank: 576,752
Average Customer Rating: 5 out of 5
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Customer ReviewsRating: 5 out of 5
Well balanced!
The authors of this well balanced textbook succeed admirably well in teaching the subject to the union of students in math and in cs, and to engineers. The danger with subjects that cut accross fields is that they might appeal to the intersection of audiences involved rather than to the much larger union. The authors seem to be at home with all the types of readers, they realize that the lingo and the aim is different for the different and diverse groups of students. Indeed, the tools of information theory, data compression, and arithmetic coding are widely used in science. While the mathematical parts of the subject is old[Shannon, Kolmogorov..., measurements of information, entropy, channel capacity], the applications are still going strong, with new things coming out at a fast rate right up to the present. So the emphasis in the book on data and image compression is very appropriate. There is even a JPEGtool user's guide in the appendix.
Rating: 5 out of 5
Best Book on Compression
I read a lot of books on Compression, but this is indeed the best one I ever bought. I love this book and read it frequently.
Rating: 5 out of 5
Great Book on Compression
I am a gradute student in computer science and I have read a lot of books on this subject, including 1- Digital Image Compression, by Weidong Kou, 2- The Data Compression Book, by Mark Nelson, 3- JPEG Still Image Data Compression Standard, by Pennebaker. I have also browsed few other books on this subject, but one thing I can say for sure, that this is the best book ever written on the subject of Compression. It explains the information theory and data Compression in the best possible way, with best examples. Once read, you will never forget the algorithms. I just love this book, and read it every once in a while.
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