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Covering the full range of channel codes from the most conventional through to the most advanced, the second edition of Turbo Coding, Turbo Equalisation and Space-Time Coding is a self-contained reference on channel coding for wireless channels. The book commences with a historical perspective on the topic, which leads to two basic component codes, convolutional and block codes. It then moves on to turbo codes which exploit iterative decoding by using algorithms, such as the Maximum-A-Posteriori (MAP), Log-MAP and Soft Output Viterbi Algorithm (SOVA), comparing their performance. It also compares Trellis Coded Modulation (TCM), Turbo Trellis Coded Modulation (TTCM), Bit-Interleaved Coded Modulation (BICM) and Iterative BICM (BICM-ID) under various channel conditions.The horizon of the content is then extended to incorporate topics which have found their way into diverse standard systems. These include space-time block and trellis codes, as well as other Multiple-Input Multiple-Output (MIMO) schemes and near-instantaneously Adaptive Quadrature Amplitude Modulation (AQAM). The book also elaborates on turbo equalisation by providing a detailed portrayal of recent advances in partial response modulation schemes using diverse channel codes.A radically new aspect for this second edition is the discussion of multi-level coding and sphere-packing schemes, Extrinsic Information Transfer (EXIT) charts, as well as an introduction to the family of Generalized Low Density Parity Check codes.. This new edition includes recent advances in near-capacity turbo-transceivers as well as new sections on multi-level coding schemes and of Generalized Low Density Parity Check codes. Comparatively studies diverse channel coded and turbo detected systems to give all-inclusive information for researchers, engineers and students. Details EXIT-chart based irregular transceiver designs. Uses rich performance comparisons as well as diverse near-capacity design examples.

Coding theory. --- Iterative methods (Mathematics) --- Signal processing --- Mathematics.

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Suitable as supplemental reading in courses in differential and integral calculus, numerical analysis, approximation theory and computer-aided geometric design. Relations of mathematical objects to each other are expressed by transformations. The repeated application of a transformation over and over again, i.e., its iteration leads to solution of equations, as in Newton's method for finding roots, or Picard's method for solving differential equations. This book studies a treasure trove of iterations, in number theory, analysis and geometry, and applied them to various problems, many of them taken from international and national Mathematical Olympiad competitions. Among topics treated are classical and not so classical inequalities, Sharkovskii's theorem, interpolation, Bernstein polynomials, BŽzier curves and surfaces, and splines. Most of the book requires only high school mathematics; the last part requires elementary calculus. This book would be an excellent supplement to courses in calculus, differential equations,, numerical analysis, approximation theory and computer-aided geometric design.

Iterative methods (Mathematics) --- Transformations (Mathematics) --- Algorithms --- Differential invariants --- Geometry, Differential --- Iteration (Mathematics) --- Numerical analysis --- Iterative methods (Mathematics). --- Transformations (Mathematics).

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With the advent of approximation algorithms for NP-hard combinatorial optimization problems, several techniques from exact optimization such as the primal-dual method have proven their staying power and versatility. This book describes a simple and powerful method that is iterative in essence and similarly useful in a variety of settings for exact and approximate optimization. The authors highlight the commonality and uses of this method to prove a variety of classical polyhedral results on matchings, trees, matroids and flows. The presentation style is elementary enough to be accessible to anyone with exposure to basic linear algebra and graph theory, making the book suitable for introductory courses in combinatorial optimization at the upper undergraduate and beginning graduate levels. Discussions of advanced applications illustrate their potential for future application in research in approximation algorithms.

Iterative methods (Mathematics) --- Combinatorial optimization --- Itération (Mathématiques) --- Optimisation combinatoire --- Combinatorial optimization. --- Optimization, Combinatorial --- Combinatorial analysis --- Mathematical optimization --- Iteration (Mathematics) --- Numerical analysis --- Iterative methods (Mathematics).

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Iterative methods (Mathematics) --- Algorithms. --- Numerical analysis. --- Mathematical analysis --- Algorism --- Algebra --- Arithmetic --- Iteration (Mathematics) --- Numerical analysis --- Foundations

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Deep learning (Machine learning). --- Learning, Deep (Machine learning) --- Iterative methods (Mathematics) --- Machine learning