Convex Optimization for Signal Processing and Communications: From Fundamentals to Applications, Chi Chong-Yung, Li Wei-Chiang, Lin Chia-Hsiang
Название: Selected Applications of Convex Optimization ISBN: 3662463555 ISBN-13(EAN): 9783662463550 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book focuses on the applications of convex optimization and highlights several topics, including support vector machines, parameter estimation, norm approximation and regularization, semi-definite programming problems, convex relaxation, and geometric problems.
Автор: Juditsky Anatoli, Nemirovski Arkadi Название: Statistical Inference Via Convex Optimization ISBN: 0691197296 ISBN-13(EAN): 9780691197296 Издательство: Wiley Рейтинг: Цена: 13939.00 р. Наличие на складе: Поставка под заказ.
Описание:
This authoritative book draws on the latest research to explore the interplay of high-dimensional statistics with optimization. Through an accessible analysis of fundamental problems of hypothesis testing and signal recovery, Anatoli Juditsky and Arkadi Nemirovski show how convex optimization theory can be used to devise and analyze near-optimal statistical inferences.
Statistical Inference via Convex Optimization is an essential resource for optimization specialists who are new to statistics and its applications, and for data scientists who want to improve their optimization methods. Juditsky and Nemirovski provide the first systematic treatment of the statistical techniques that have arisen from advances in the theory of optimization. They focus on four well-known statistical problems--sparse recovery, hypothesis testing, and recovery from indirect observations of both signals and functions of signals--demonstrating how they can be solved more efficiently as convex optimization problems. The emphasis throughout is on achieving the best possible statistical performance. The construction of inference routines and the quantification of their statistical performance are given by efficient computation rather than by analytical derivation typical of more conventional statistical approaches. In addition to being computation-friendly, the methods described in this book enable practitioners to handle numerous situations too difficult for closed analytical form analysis, such as composite hypothesis testing and signal recovery in inverse problems.
Statistical Inference via Convex Optimization features exercises with solutions along with extensive appendixes, making it ideal for use as a graduate text.
Описание: This cutting-edge book is a clear and thorough exposition of signal-processing fundamentals for communications and major sensing systems. Based on the author’s earlier book in this area, this revised and expanded resource offers you expert guidance in the detection of optical, acoustic and radio-frequency signals in noise. It covers digital filtering and parameter estimation, and helps you with problems associated with radar system design, including search, tracking and measurement ambiguity.
Автор: Marzetta Название: Fundamentals of Massive MIMO ISBN: 1107175577 ISBN-13(EAN): 9781107175570 Издательство: Cambridge Academ Рейтинг: Цена: 11405.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Written by the concept`s pioneers, this is the first complete guide to the physical and engineering principles of Massive MIMO. Richly illustrated by numerous case studies, it covers key topics such as propagation models, channel modeling, and cell analysis, and stresses capacity bounds. Problem sets and solutions are provided online.
Автор: Nicolas Hadjisavvas; Panos M. Pardalos Название: Advances in Convex Analysis and Global Optimization ISBN: 0792369424 ISBN-13(EAN): 9780792369424 Издательство: Springer Рейтинг: Цена: 25155.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A conference on Convex Analysis and Global Optimization was held in 2000 in Greece in honour of the memory of C. Caratheodory (1873-1950). This volume contains a selection of papers based on talks presented at the conference. The two themes of convexity and global optimization pervade the book.
Автор: Pardalos Panos M., Zilinskas Antanas, Zilinskas Julius Название: Non-Convex Multi-Objective Optimization ISBN: 3319869817 ISBN-13(EAN): 9783319869810 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Recent results on non-convex multi-objective optimization problems and methods are presented in this book, with particular attention to expensive black-box objective functions.
Описание: This two-volume work introduces the theory and applications of Schur-convex functions. The second volume mainly focuses on the application of Schur-convex functions in sequences inequalities, integral inequalities, mean value inequalities for two variables, mean value inequalities for multi-variables, and in geometric inequalities.
Автор: Hazan, Elad Название: Introduction to online convex optimization ISBN: 1680831704 ISBN-13(EAN): 9781680831702 Издательство: Неизвестно Рейтинг: Цена: 22760.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Focuses on optimization as a process. This book is intended to serve as a reference for a self-contained course on online convex optimization and the convex optimization approach to machine learning for the educated graduate student in computer science/electrical engineering/operations research/statistics and related fields.
Описание: Stefan Rocktaschel introduces a branch-and-bound algorithm that determines a cover of the efficient set of multiobjective mixed-integer convex optimization problems. He examines particular steps of this algorithm in detail and enhances the basic algorithm with additional modifications that ensure a more precise cover of the efficient set.
Автор: Panos M. Pardalos; Antanas ?ilinskas; Julius ?ilin Название: Non-Convex Multi-Objective Optimization ISBN: 3319610058 ISBN-13(EAN): 9783319610054 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Recent results on non-convex multi-objective optimization problems and methods are presented in this book, with particular attention to expensive black-box objective functions.
Автор: Roman G. Strongin; Yaroslav D. Sergeyev Название: Global Optimization with Non-Convex Constraints ISBN: 0792364902 ISBN-13(EAN): 9780792364900 Издательство: Springer Рейтинг: Цена: 43184.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents a new approach to global non-convex constrained optimization. Problem dimensionality is reduced via space-filling curves and to economize the search, constraint is accounted separately (penalties are not employed). The multicriteria case is also considered.
Описание: This two-volume work introduces the theory and applications of Schur-convex functions. The first volume introduces concepts and properties of Schur-convex functions, including Schur-geometrically convex functions, Schur-harmonically convex functions, Schur-power convex functions, etc. and also discusses applications of Schur-convex functions in symmetric function inequalities.
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