We live in an information society. This book describes the basic ideas of information theory, showing how we can transmit and store information as compactly as possible, how much information can be transmitted by a particular channel or network, and how security can be assured. It covers all the basic ideas of information theory and sets them in the context of current applications. These include Shannon's information measure, discrete and continuous information sources and information channels with or without memory, source and channel decoding, rate distortion theory, error correcting codes and the information theoretical approach to cryptology. Throughout the book the author has paid special attention to multiterminal or network information theory. This text will be of interest to advanced undergraduates and graduate students in electrical engineering, computer science, informatics, mathematics, physics and management sciences.
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"Lubbe's thorough discourse on the topic of information theory is very complete and classical in nature...The coverage of material is consistent and complete." Choice
Language Notes
Text: English (translation)
Original Language: Dutch --This text refers to an out of print or unavailable edition of this title.
Original Language: Dutch --This text refers to an out of print or unavailable edition of this title.
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Inside This Book
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First Sentence:
Information theory is the science which deals with the concept 'information', its measurement and its applications. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
key appearance equivocation, source output symbols, most probable messages, message equivocation, symbol probability code, key equivocation, continuous information source, unicity distance, discrete information source, absolute redundancy, conditional amount, continuous stochastic variable, rate distortion bound, rate distortion function, arbitrarily small error probability, binary erasure channel, source coding theorem, memoryless source, substitution alphabet, average error probability, channel coding theorem, possible code words, following transition matrix, source alphabet, autocovariance matrix New!
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Information theory is the science which deals with the concept 'information', its measurement and its applications. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
key appearance equivocation, source output symbols, most probable messages, message equivocation, symbol probability code, key equivocation, continuous information source, unicity distance, discrete information source, absolute redundancy, conditional amount, continuous stochastic variable, rate distortion bound, rate distortion function, arbitrarily small error probability, binary erasure channel, source coding theorem, memoryless source, substitution alphabet, average error probability, channel coding theorem, possible code words, following transition matrix, source alphabet, autocovariance matrix 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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26
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- Information Theory (Dover Phoenix Editions) by Stanford Goldman in Back Matter
- Uncertainty in Knowledge Bases: 3rd International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, ... (Lecture Notes in Computer Science) by Bernadette Bouchon-Meunier on page 376, and page 392
- Philosophy and Computing: An Introduction by Luciano Floridi in Back Matter (1), and Back Matter (2)
- Basic Methods of Cryptography by Jan C. A. van der Lubbe in Back Matter (1), and Back Matter (2)
- Fundamentals of Information Theory and Coding Design (Discrete Mathematics and Its Applications) by Roberto Togneri on page 169, and page 234
- Entropy Measures, Maximum Entropy Principle and Emerging Applications (Studies in Fuzziness and Soft Computing) by Karmeshu on page 47
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