Concentration of Measure Inequalities in Information Theory, Communications and Coding (Foundations and Trends(r) in Communications and Information)

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9781601987242: Concentration of Measure Inequalities in Information Theory, Communications and Coding (Foundations and Trends(r) in Communications and Information)

Concentration inequalities have been the subject of exciting developments during the last two decades, and have been intensively studied and used as a powerful tool in various areas. These include convex geometry, functional analysis, statistical physics, mathematical statistics, pure and applied probability theory (e.g., concentration of measure phenomena in random graphs, random matrices, and percolation), information theory, theoretical computer science, learning theory, and dynamical systems. Concentration of Measure Inequalities in Information Theory, Communications and Coding focuses on some of the key modern mathematical tools that are used for the derivation of concentration inequalities, on their links to information theory, and on their various applications to communications and coding. In addition to being a survey, this monograph also includes various new recent results derived by the authors. Concentration of Measure Inequalities in Information Theory, Communications and Coding is essential reading for all researchers and scientists in information theory and coding.

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Igal Sason; Maxim Raginsky; Sason Sason
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Book Description Now Publishers Inc, United States, 2013. Paperback. Book Condition: New. 232 x 156 mm. Language: English . Brand New Book. Concentration inequalities have been the subject of exciting developments during the last two decades, and have been intensively studied and used as a powerful tool in various areas. These include convex geometry, functional analysis, statistical physics, mathematical statistics, pure and applied probability theory (e.g., concentration of measure phenomena in random graphs, random matrices, and percolation), information theory, theoretical computer science, learning theory, and dynamical systems. Concentration of Measure Inequalities in Information Theory, Communications and Coding focuses on some of the key modern mathematical tools that are used for the derivation of concentration inequalities, on their links to information theory, and on their various applications to communications and coding. In addition to being a survey, this monograph also includes various new recent results derived by the authors. Concentration of Measure Inequalities in Information Theory, Communications and Coding is essential reading for all researchers and scientists in information theory and coding. Bookseller Inventory # LIB9781601987242

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Igal Sason; Maxim Raginsky; Sason Sason
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Book Description Now Publishers Inc, United States, 2013. Paperback. Book Condition: New. 232 x 156 mm. Language: English . Brand New Book. Concentration inequalities have been the subject of exciting developments during the last two decades, and have been intensively studied and used as a powerful tool in various areas. These include convex geometry, functional analysis, statistical physics, mathematical statistics, pure and applied probability theory (e.g., concentration of measure phenomena in random graphs, random matrices, and percolation), information theory, theoretical computer science, learning theory, and dynamical systems. Concentration of Measure Inequalities in Information Theory, Communications and Coding focuses on some of the key modern mathematical tools that are used for the derivation of concentration inequalities, on their links to information theory, and on their various applications to communications and coding. In addition to being a survey, this monograph also includes various new recent results derived by the authors. Concentration of Measure Inequalities in Information Theory, Communications and Coding is essential reading for all researchers and scientists in information theory and coding. Bookseller Inventory # LIB9781601987242

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Book Description Transatlantic Publishers Okt 2013, 2013. Taschenbuch. Book Condition: Neu. 233x154x20 mm. Neuware - Concentration inequalities have been the subject of exciting developments during the last two decades, and have been intensively studied and used as a powerful tool in various areas. These include convex geometry, functional analysis, statistical physics, mathematical statistics, pure and applied probability theory (e.g., concentration of measure phenomena in random graphs, random matrices, and percolation), information theory, theoretical computer science, learning theory, and dynamical systems. Concentration of Measure Inequalities in Information Theory, Communications and Coding focuses on some of the key modern mathematical tools that are used for the derivation of concentration inequalities, on their links to information theory, and on their various applications to communications and coding. In addition to being a survey, this monograph also includes various new recent results derived by the authors. Concentration of Measure Inequalities in Information Theory, Communications and Coding is essential reading for all researchers and scientists in information theory and coding. 248 pp. Englisch. Bookseller Inventory # 9781601987242

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Book Description Transatlantic Publishers Okt 2013, 2013. Taschenbuch. Book Condition: Neu. 233x154x20 mm. Neuware - Concentration inequalities have been the subject of exciting developments during the last two decades, and have been intensively studied and used as a powerful tool in various areas. These include convex geometry, functional analysis, statistical physics, mathematical statistics, pure and applied probability theory (e.g., concentration of measure phenomena in random graphs, random matrices, and percolation), information theory, theoretical computer science, learning theory, and dynamical systems. Concentration of Measure Inequalities in Information Theory, Communications and Coding focuses on some of the key modern mathematical tools that are used for the derivation of concentration inequalities, on their links to information theory, and on their various applications to communications and coding. In addition to being a survey, this monograph also includes various new recent results derived by the authors. Concentration of Measure Inequalities in Information Theory, Communications and Coding is essential reading for all researchers and scientists in information theory and coding. 248 pp. Englisch. Bookseller Inventory # 9781601987242

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Book Description Transatlantic Publishers Okt 2013, 2013. Taschenbuch. Book Condition: Neu. 233x154x20 mm. Neuware - Concentration inequalities have been the subject of exciting developments during the last two decades, and have been intensively studied and used as a powerful tool in various areas. These include convex geometry, functional analysis, statistical physics, mathematical statistics, pure and applied probability theory (e.g., concentration of measure phenomena in random graphs, random matrices, and percolation), information theory, theoretical computer science, learning theory, and dynamical systems. Concentration of Measure Inequalities in Information Theory, Communications and Coding focuses on some of the key modern mathematical tools that are used for the derivation of concentration inequalities, on their links to information theory, and on their various applications to communications and coding. In addition to being a survey, this monograph also includes various new recent results derived by the authors. Concentration of Measure Inequalities in Information Theory, Communications and Coding is essential reading for all researchers and scientists in information theory and coding. 248 pp. Englisch. Bookseller Inventory # 9781601987242

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Book Description Transatlantic Publishers Okt 2013, 2013. Taschenbuch. Book Condition: Neu. 233x154x20 mm. Neuware - Concentration inequalities have been the subject of exciting developments during the last two decades, and have been intensively studied and used as a powerful tool in various areas. These include convex geometry, functional analysis, statistical physics, mathematical statistics, pure and applied probability theory (e.g., concentration of measure phenomena in random graphs, random matrices, and percolation), information theory, theoretical computer science, learning theory, and dynamical systems. Concentration of Measure Inequalities in Information Theory, Communications and Coding focuses on some of the key modern mathematical tools that are used for the derivation of concentration inequalities, on their links to information theory, and on their various applications to communications and coding. In addition to being a survey, this monograph also includes various new recent results derived by the authors. Concentration of Measure Inequalities in Information Theory, Communications and Coding is essential reading for all researchers and scientists in information theory and coding. 248 pp. Englisch. Bookseller Inventory # 9781601987242

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Book Description Transatlantic Publishers Okt 2013, 2013. Taschenbuch. Book Condition: Neu. 233x154x20 mm. Neuware - Concentration inequalities have been the subject of exciting developments during the last two decades, and have been intensively studied and used as a powerful tool in various areas. These include convex geometry, functional analysis, statistical physics, mathematical statistics, pure and applied probability theory (e.g., concentration of measure phenomena in random graphs, random matrices, and percolation), information theory, theoretical computer science, learning theory, and dynamical systems. Concentration of Measure Inequalities in Information Theory, Communications and Coding focuses on some of the key modern mathematical tools that are used for the derivation of concentration inequalities, on their links to information theory, and on their various applications to communications and coding. In addition to being a survey, this monograph also includes various new recent results derived by the authors. Concentration of Measure Inequalities in Information Theory, Communications and Coding is essential reading for all researchers and scientists in information theory and coding. 248 pp. Englisch. Bookseller Inventory # 9781601987242

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