Author: Saejoon KimPublisher:
ISBN:
Category :
Languages : en
Pages : 278
Book Description
Probabilistic Reasoning, Parameter Estimation and Issues in Turbo Decoding
Author: Saejoon KimTurbo Coding
Author: Chris HeegardPublisher: Springer Science & Business Media
ISBN: 1475729995
Category : Technology & Engineering
Languages : en
Pages : 226
Book Description
When the 50th anniversary of the birth of Information Theory was celebrated at the 1998 IEEE International Symposium on Informa tion Theory in Boston, there was a great deal of reflection on the the year 1993 as a critical year. As the years pass and more perspec tive is gained, it is a fairly safe bet that we will view 1993 as the year when the "early years" of error control coding came to an end. This was the year in which Berrou, Glavieux and Thitimajshima pre sented "Near Shannon Limit Error-Correcting Coding and Decoding: Turbo Codes" at the International Conference on Communications in Geneva. In their presentation, Berrou et al. claimed that a combi nation of parallel concatenation and iterative decoding can provide reliable communications at a signal to noise ratio that is within a few tenths of a dB of the Shannon limit. Nearly fifty years of striving to achieve the promise of Shannon's noisy channel coding theorem had come to an end. The implications of this result were immediately apparent to all -coding gains on the order of 10 dB could be used to dramatically extend the range of communication receivers, increase data rates and services, or substantially reduce transmitter power levels. The 1993 ICC paper set in motion several research efforts that have permanently changed the way we look at error control coding.
Fundamentals of Codes, Graphs, and Iterative Decoding
Author: Stephen B. WickerPublisher: Springer Science & Business Media
ISBN: 0306477947
Category : Technology & Engineering
Languages : en
Pages : 241
Book Description
Fundamentals of Codes, Graphs, and Iterative Decoding is an explanation of how to introduce local connectivity, and how to exploit simple structural descriptions. Chapter 1 provides an overview of Shannon theory and the basic tools of complexity theory, communication theory, and bounds on code construction. Chapters 2 - 4 provide an overview of "classical" error control coding, with an introduction to abstract algebra, and block and convolutional codes. Chapters 5 - 9 then proceed to systematically develop the key research results of the 1990s and early 2000s with an introduction to graph theory, followed by chapters on algorithms on graphs, turbo error control, low density parity check codes, and low density generator codes.
Turbo Codes and Interleaver Design
Author: Kenneth Skilling AndrewsPublisher:
ISBN:
Category :
Languages : en
Pages : 348
Book Description
American Doctoral Dissertations
Author: Publisher:
ISBN:
Category : Dissertation abstracts
Languages : en
Pages : 784
Book Description
Dissertation Abstracts International
Author: Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 830
Book Description
Parameter Estimation
Author: H. W SorensonPublisher:
ISBN:
Category : Parameter estimation
Languages : en
Pages : 382
Book Description
Parameter Estimation in Engineering and Science
Author: James Vere BeckPublisher: John Wiley & Sons
ISBN:
Category : Engineering
Languages : en
Pages : 544
Book Description
Introduction to and survey of parameter estimation; Probability; Introduction to statistics; Parameter estimation methods; Introduction to linear estimation; Matrix analysis for linear parameter estimation; Minimization of sum of squares functions for models nonlinear in parameters; Design of optimal experiments.
Information Theory, Inference and Learning Algorithms
Author: David J. C. MacKayPublisher: Cambridge University Press
ISBN: 9780521642989
Category : Computers
Languages : en
Pages : 694
Book Description
Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.
Author: