Algorithmic Information Theory treats the mathematics of many important areas in digital information processing. It has been written as a read-and-learn book on concrete mathematics, for teachers, students and practitioners in electronic engineering, computer science and mathematics. The presentation is dense, and the examples and exercises are numerous. It is based on lectures on information technology (Data Compaction, Cryptography, Polynomial Coding) for engineers.
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Editorial Reviews
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From the reviews: "This book, consisting of five chapters, deals with information processing. … The format of chapters … is very good. … It is very readable and provides a valuable source about information processing. This is a good book on the subject … . it is a welcome addition." (Arjun K. Gupta, Zentralblatt MATH, Vol. 1136 (14), 2008)
From the Back Cover
This book treats the Mathematics of many important areas in digital information processing. It covers, in a unified presentation, five topics: Data Compression, Cryptography, Sampling (Signal Theory), Error Control Codes, Data Reduction. The thematic choices are practice-oriented. So, the important final part of the book deals with the Discrete Cosine Transform and the Discrete Wavelet Transform, acting in image compression. The presentation is dense, the examples and numerous exercises are concrete. The pedagogic architecture follows increasing mathematical complexity. A read-and-learn book on Concrete Mathematics, for teachers, students and practitioners in Electronic Engineering, Computer Science and Mathematics.
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Inside This Book
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First Sentence:
This book deals with information processing; so it is far from being a book on information theory (which would be built on description and estimation). Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
arithmetic code word, information bitstream, interior algorithm, biorthogonal wavelet bases, filter hank, perfect reconstruction filter bank, binary positions, trigonometric interpolation, current string, signal theory, state array, quantized coefficients, discrete wavelet transform, convolutional code, circular convolution, round keys, binary words, binary notation Key Phrases - Capitalized Phrases (CAPs): (learn more)
Lossy Compression, Data Reduction, Discrete Wavelet Transform, Discrete Fourier Transform, Convolution Theorem, Reed Solomon, Sampling Theorem, Discrete Cosine Transform, Entropy Coding, Exercise Show, Linear Algebra, Proposition Let, Data Beduction, Remark Let New!
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
This book deals with information processing; so it is far from being a book on information theory (which would be built on description and estimation). Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
arithmetic code word, information bitstream, interior algorithm, biorthogonal wavelet bases, filter hank, perfect reconstruction filter bank, binary positions, trigonometric interpolation, current string, signal theory, state array, quantized coefficients, discrete wavelet transform, convolutional code, circular convolution, round keys, binary words, binary notation Key Phrases - Capitalized Phrases (CAPs): (learn more)
Lossy Compression, Data Reduction, Discrete Wavelet Transform, Discrete Fourier Transform, Convolution Theorem, Reed Solomon, Sampling Theorem, Discrete Cosine Transform, Entropy Coding, Exercise Show, Linear Algebra, Proposition Let, Data Beduction, Remark Let New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
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