Rudolf Ahlswede's Books

Probabilistic Methods and Distributed Information

Rudolf Ahlswede’s Lectures on Information Theory 5

By: Rudolf Ahlswede

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Probabilistic Methods and Distributed Information

Rudolf Ahlswede’s Lectures on Information Theory 5

By: Rudolf Ahlswede

The fifth volume of Rudolf Ahlswede’s lectures on Information Theory focuses on several problems that were at the heart of a lot of his research. One of the highlights of the entire lecture note series is surely Part I of this volume on arbitrarily varying channels (AVC), a subject in which Ahlswede was probably the world's leading expert. Appended to Part I is a survey by Holger Boche and Ahmed Mansour on recent results concerning AVC and arbitrarily varying wiretap channels (AVWC). After a short Part II on continuous data compression, Part III, the longest part of the book, is devoted to distributed information. This Part includes discussions on a variety of related topics; among them let us emphasize two which are famously associated with Ahlswede: "multiple descriptions", on which he produced some of the best research worldwide, and "network coding", which had Ahlswede among the authors of its pioneering paper. The final Part IV on "Statistical Inference under Communication constraints" is mainly based on Ahlswede’s joint paper with Imre Csiszar, which received the Best Paper Award of the IEEE Information Theory Society. The lectures presented in this work, which consists of 10 volumes, are suitable for graduate students in Mathematics, and also for those working in Theoretical Computer Science, Physics, and Electrical Engineering with a background in basic Mathematics. The lectures can be used either as the basis for courses or to supplement them in many ways. Ph.D. students will also find research problems, often with conjectures, that offer potential subjects for a thesis. More advanced researchers may find questions which form the basis of entire research programs.

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581

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Springer

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ISBN 10

3030003124

ISBN 13

9783030003128

Identification and Other Probabilistic Models

Rudolf Ahlswede’s Lectures on Information Theory 6

By: Rudolf Ahlswede

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Identification and Other Probabilistic Models

Rudolf Ahlswede’s Lectures on Information Theory 6

By: Rudolf Ahlswede

The sixth volume of Rudolf Ahlswede's lectures on Information Theory is focused on Identification Theory. In contrast to Shannon's classical coding scheme for the transmission of a message over a noisy channel, in the theory of identification the decoder is not really interested in what the received message is, but only in deciding whether a message, which is of special interest to him, has been sent or not. There are also algorithmic problems where it is not necessary to calculate the solution, but only to check whether a certain given answer is correct. Depending on the problem, this answer might be much easier to give than finding the solution. ``Easier'' in this context means using fewer resources like channel usage, computing time or storage space. Ahlswede and Dueck's main result was that, in contrast to transmission problems, where the possible code sizes grow exponentially fast with block length, the size of identification codes will grow doubly exponentially fast. The theory of identification has now developed into a sophisticated mathematical discipline with many branches and facets, forming part of the Post Shannon theory in which Ahlswede was one of the leading experts. New discoveries in this theory are motivated both by concrete engineering problems and by explorations of the inherent properties of the mathematical structures. Rudolf Ahlswede wrote: It seems that the whole body of present day Information Theory will undergo serious revisions and some dramatic expansions. In this book we will open several directions of future research and start the mathematical description of communication models in great generality. For some specific problems we provide solutions or ideas for their solutions. The lectures presented in this work, which consists of 10 volumes, are suitable for graduate students in Mathematics, and also for those working in Theoretical Computer Science, Physics, and Electrical Engineering with a background in basic Mathematics. The lectures can be used as the basis for courses or to supplement courses in many ways. Ph.D. students will also find research problems, often with conjectures, that offer potential subjects for a thesis. More advanced researchers may find questions which form the basis of entire research programs. The book also contains an afterword by Gunter Dueck.

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720

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Springer Nature

Published Date

ISBN 10

3030650723

ISBN 13

9783030650728

Transmitting and Gaining Data

Rudolf Ahlswede’s Lectures on Information Theory 2

By: Rudolf Ahlswede

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Transmitting and Gaining Data

Rudolf Ahlswede’s Lectures on Information Theory 2

By: Rudolf Ahlswede

The calculation of channel capacities was one of Rudolf Ahlswede's specialties and is the main topic of this second volume of his Lectures on Information Theory. Here we find a detailed account of some very classical material from the early days of Information Theory, including developments from the USA, Russia, Hungary and (which Ahlswede was probably in a unique position to describe) the German school centered around his supervisor Konrad Jacobs. These lectures made an approach to a rigorous justification of the foundations of Information Theory. This is the second of several volumes documenting Rudolf Ahlswede's lectures on Information Theory. Each volume includes comments from an invited well-known expert. In the supplement to the present volume, Gerhard Kramer contributes his insights. Classical information processing concerns the main tasks of gaining knowledge and the storage, transmission and hiding of data. The first task is the prime goal of Statistics. For transmission and hiding data, Shannon developed an impressive mathematical theory called Information Theory, which he based on probabilistic models. The theory largely involves the concept of codes with small error probabilities in spite of noise in the transmission, which is modeled by channels. The lectures presented in this work are suitable for graduate students in Mathematics, and also for those working in Theoretical Computer Science, Physics, and Electrical Engineering with a background in basic Mathematics. The lectures can be used as the basis for courses or to supplement courses in many ways. Ph.D. students will also find research problems, often with conjectures, that offer potential subjects for a thesis. More advanced researchers may find questions which form the basis of entire research programs.

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471

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ISBN 10

3319125230

ISBN 13

9783319125237

Storing and Transmitting Data

Rudolf Ahlswede’s Lectures on Information Theory 1

By: Rudolf Ahlswede

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Storing and Transmitting Data

Rudolf Ahlswede’s Lectures on Information Theory 1

By: Rudolf Ahlswede

The volume “Storing and Transmitting Data” is based on Rudolf Ahlswede's introductory course on "Information Theory I" and presents an introduction to Shannon Theory. Readers, familiar or unfamiliar with the technical intricacies of Information Theory, will benefit considerably from working through the book; especially Chapter VI with its lively comments and uncensored insider views from the world of science and research offers informative and revealing insights. This is the first of several volumes that will serve as a collected research documentation of Rudolf Ahlswede’s lectures on information theory. Each volume includes comments from an invited well-known expert. Holger Boche contributed his insights in the supplement of the present volume. Classical information processing concerns the main tasks of gaining knowledge, storage, transmitting and hiding data. The first task is the prime goal of Statistics. For the two next, Shannon presented an impressive mathematical theory called Information Theory, which he based on probabilistic models. The theory largely involves the concept of codes with small error probabilities in spite of noise in the transmission, which is modeled by channels. The lectures presented in this work are suitable for graduate students in Mathematics, and also in Theoretical Computer Science, Physics, and Electrical Engineering with background in basic Mathematics. The lectures can be used as the basis for courses or to supplement courses in many ways. Ph.D. students will also find research problems, often with conjectures, that offer potential subjects for a thesis. More advanced researchers may find the basis of entire research programs.

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Page Count

304

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Springer Science & Business Media

Published Date

ISBN 10

3319054791

ISBN 13

9783319054797

Hiding Data - Selected Topics

Rudolf Ahlswede’s Lectures on Information Theory 3

By: Rudolf Ahlswede

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Hiding Data - Selected Topics

Rudolf Ahlswede’s Lectures on Information Theory 3

By: Rudolf Ahlswede

Devoted to information security, this volume begins with a short course on cryptography, mainly based on lectures given by Rudolf Ahlswede at the University of Bielefeld in the mid 1990s. It was the second of his cycle of lectures on information theory which opened with an introductory course on basic coding theorems, as covered in Volume 1 of this series. In this third volume, Shannon’s historical work on secrecy systems is detailed, followed by an introduction to an information-theoretic model of wiretap channels, and such important concepts as homophonic coding and authentication. Once the theoretical arguments have been presented, comprehensive technical details of AES are given. Furthermore, a short introduction to the history of public-key cryptology, RSA and El Gamal cryptosystems is provided, followed by a look at the basic theory of elliptic curves, and algorithms for efficient addition in elliptic curves. Lastly, the important topic of “oblivious transfer” is discussed, which is strongly connected to the privacy problem in communication. Today, the importance of this problem is rapidly increasing, and further research and practical realizations are greatly anticipated. This is the third of several volumes serving as the collected documentation of Rudolf Ahlswede’s lectures on information theory. Each volume includes comments from an invited well-known expert. In the supplement to the present volume, Rüdiger Reischuk contributes his insights. Classical information processing concerns the main tasks of gaining knowledge and the storage, transmission and hiding of data. The first task is the prime goal of Statistics. For transmission and hiding data, Shannon developed an impressive mathematical theory called Information Theory, which he based on probabilistic models. The theory largely involves the concept of codes with small error probabilities in spite of noise in the transmission, which is modeled by channels. The lectures presented in this work are suitable for graduate students in Mathematics, and also for those working in Theoretical Computer Science, Physics, and Electrical Engineering with a background in basic Mathematics. The lectures can be used as the basis for courses or to supplement courses in many ways. Ph.D. students will also find research problems, often with conjectures, that offer potential subjects for a thesis. More advanced researchers may find questions which form the basis of entire research programs.

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Page Count

367

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Springer

Published Date

ISBN 10

3319315153

ISBN 13

9783319315157

Combinatorial Methods and Models

Rudolf Ahlswede’s Lectures on Information Theory 4

By: Rudolf Ahlswede

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Combinatorial Methods and Models

Rudolf Ahlswede’s Lectures on Information Theory 4

By: Rudolf Ahlswede

The fourth volume of Rudolf Ahlswede’s lectures on Information Theory is focused on Combinatorics. Ahlswede was originally motivated to study combinatorial aspects of Information Theory via zero-error codes: in this case the structure of the coding problems usually drastically changes from probabilistic to combinatorial. The best example is Shannon’s zero error capacity, where independent sets in graphs have to be examined. The extension to multiple access channels leads to the Zarankiewicz problem. A code can be regarded combinatorially as a hypergraph; and many coding theorems can be obtained by appropriate colourings or coverings of the underlying hypergraphs. Several such colouring and covering techniques and their applications are introduced in this book. Furthermore, codes produced by permutations and one of Ahlswede’s favourite research fields -- extremal problems in Combinatorics -- are presented. Whereas the first part of the book concentrates on combinatorial methods in order to analyse classical codes as prefix codes or codes in the Hamming metric, the second is devoted to combinatorial models in Information Theory. Here the code concept already relies on a rather combinatorial structure, as in several concrete models of multiple access channels or more refined distortions. An analytical tool coming into play, especially during the analysis of perfect codes, is the use of orthogonal polynomials. Classical information processing concerns the main tasks of gaining knowledge and the storage, transmission and hiding of data. The first task is the prime goal of Statistics. For transmission and hiding data, Shannon developed an impressive mathematical theory called Information Theory, which he based on probabilistic models. The theory largely involves the concept of codes with small error probabilities in spite of noise in the transmission, which is modeled by channels. The lectures presented in this work are suitable for graduate students in Mathematics, and also for those working in Theoretical Computer Science, Physics, and Electrical Engineering with a background in basic Mathematics. The lectures can be used as the basis for courses or to supplement courses in many ways. Ph.D. students will also find research problems, often with conjectures, that offer potential subjects for a thesis. More advanced researchers may find questions which form the basis of entire research programs.

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Page Count

395

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Springer

Published Date

ISBN 10

3319531395

ISBN 13

9783319531397

Probabilistic Methods and Distributed Information

Rudolf Ahlswede’s Lectures on Information Theory 5

By: Rudolf Ahlswede

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Probabilistic Methods and Distributed Information

Rudolf Ahlswede’s Lectures on Information Theory 5

By: Rudolf Ahlswede

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581

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ISBN 10

3030003124

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9783030003128

Transmitting and Gaining Data

Rudolf Ahlswede’s Lectures on Information Theory 2

By: Rudolf Ahlswede

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Transmitting and Gaining Data

Rudolf Ahlswede’s Lectures on Information Theory 2

By: Rudolf Ahlswede

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471

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ISBN 10

3319125230

ISBN 13

9783319125237

Identification and Other Probabilistic Models

Rudolf Ahlswede’s Lectures on Information Theory 6

By: Rudolf Ahlswede

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Identification and Other Probabilistic Models

Rudolf Ahlswede’s Lectures on Information Theory 6

By: Rudolf Ahlswede

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720

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Springer Nature

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ISBN 10

3030650723

ISBN 13

9783030650728

Hiding Data - Selected Topics

Rudolf Ahlswede’s Lectures on Information Theory 3

By: Rudolf Ahlswede

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Hiding Data - Selected Topics

Rudolf Ahlswede’s Lectures on Information Theory 3

By: Rudolf Ahlswede

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Solve jigsaw puzzle

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367

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Springer

Published Date

ISBN 10

3319315153

ISBN 13

9783319315157

Combinatorial Methods and Models

Rudolf Ahlswede’s Lectures on Information Theory 4

By: Rudolf Ahlswede

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Combinatorial Methods and Models

Rudolf Ahlswede’s Lectures on Information Theory 4

By: Rudolf Ahlswede

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395

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ISBN 10

3319531395

ISBN 13

9783319531397

Storing and Transmitting Data

Rudolf Ahlswede’s Lectures on Information Theory 1

By: Rudolf Ahlswede

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Storing and Transmitting Data

Rudolf Ahlswede’s Lectures on Information Theory 1

By: Rudolf Ahlswede

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304

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Springer Science & Business Media

Published Date

ISBN 10

3319054791

ISBN 13

9783319054797

Probabilistic Methods and Distributed Information

Rudolf Ahlswede's Lectures on Information Theory 5

By: Rudolf Ahlswede

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Probabilistic Methods and Distributed Information

Rudolf Ahlswede's Lectures on Information Theory 5

By: Rudolf Ahlswede

The fifth volume of Rudolf Ahlswede's lectures on Information Theory focuses on several problems that were at the heart of a lot of his research. One of the highlights of the entire lecture note series is surely Part I of this volume on arbitrarily varying channels (AVC), a subject in which Ahlswede was probably the world's leading expert. Appended to Part I is a survey by Holger Boche and Ahmed Mansour on recent results concerning AVC and arbitrarily varying wiretap channels (AVWC). After a short Part II on continuous data compression, Part III, the longest part of the book, is devoted to distributed information. This Part includes discussions on a variety of related topics; among them let us emphasize two which are famously associated with Ahlswede: "multiple descriptions", on which he produced some of the best research worldwide, and "network coding", which had Ahlswede among the authors of its pioneering paper. The final Part IV on "Statistical Inference under Communication constraints" is mainly based on Ahlswede's joint paper with Imre Csiszar, which received the Best Paper Award of the IEEE Information Theory Society. The lectures presented in this work, which consists of 10 volumes, are suitable for graduate students in Mathematics, and also for those working in Theoretical Computer Science, Physics, and Electrical Engineering with a background in basic Mathematics. The lectures can be used either as the basis for courses or to supplement them in many ways. Ph. D. students will also find research problems, often with conjectures, that offer potential subjects for a thesis. More advanced researchers may find questions which form the basis of entire research programs.

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Published Date

ISBN 10

3030003116

ISBN 13

9783030003111

Book's by Rudolf Ahlswede

Probabilistic Methods and Distributed Information

Probabilistic Methods and Distributed Information

Identification and Other Probabilistic Models

Identification and Other Probabilistic Models

Transmitting and Gaining Data

Transmitting and Gaining Data

Storing and Transmitting Data

Storing and Transmitting Data

Hiding Data - Selected Topics

Hiding Data - Selected Topics

Combinatorial Methods and Models

Combinatorial Methods and Models

Probabilistic Methods and Distributed Information

Probabilistic Methods and Distributed Information

Transmitting and Gaining Data

Transmitting and Gaining Data

Identification and Other Probabilistic Models

Identification and Other Probabilistic Models

Hiding Data - Selected Topics

Hiding Data - Selected Topics

Combinatorial Methods and Models

Combinatorial Methods and Models

Storing and Transmitting Data

Storing and Transmitting Data

Probabilistic Methods and Distributed Information

Probabilistic Methods and Distributed Information

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