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An Introduction to Compressed Sensing, M. Vidyasagar


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Цена: 76910.00T
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Автор: M. Vidyasagar
Название:  An Introduction to Compressed Sensing
ISBN: 9781611976113
Издательство: Mare Nostrum (Eurospan)
Классификация:



ISBN-10: 1611976111
Обложка/Формат: Paperback
Страницы: 341
Вес: 0.75 кг.
Дата издания: 30.01.2020
Серия: Computational science and engineering 22
Язык: English
Размер: 181 x 255 x 24
Читательская аудитория: Professional and scholarly
Ключевые слова: Combinatorics & graph theory,Linear programming,Optimization,Probability & statistics
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Поставляется из: Англии
Описание: Compressed sensing is a relatively recent area of research that refers to the recovery of high-dimensional but low-complexity objects from a limited number of measurements. The topic has applications to signal/image processing and computer algorithms, and it draws from a variety of mathematical techniques such as graph theory, probability theory, linear algebra, and optimization. The author presents significant concepts never before discussed as well as new advances in the theory, providing an in-depth initiation to the field of compressed sensing.An Introduction to Compressed Sensing contains substantial material on graph theory and the design of binary measurement matrices, which is missing in recent texts despite being poised to play a key role in the future of compressed sensing theory. It also covers several new developments in the field and is the only book to thoroughly study the problem of matrix recovery. The book supplies relevant results alongside their proofs in a compact and streamlined presentation that is easy to navigate.The core audience for this book is engineers, computer scientists, and statisticians who are interested in compressed sensing. Professionals working in image processing, speech processing, or seismic signal processing will also find the book of interest.
Дополнительное описание: Linear programming|Probability and statistics|Combinatorics and graph theory|Optimization


Introduction to Nonparametric Estimation

Автор: Alexandre B. Tsybakov
Название: Introduction to Nonparametric Estimation
ISBN: 0387790519 ISBN-13(EAN): 9780387790510
Издательство: Springer
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Цена: 102480.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents basic nonparametric regression and density estimators and analyzes their properties. This book covers minimax lower bounds, and develops advanced topics such as: Pinsker`s theorem, oracle inequalities, Stein shrinkage, and sharp minimax adaptivity.

Elementary Probability Theory / With Stochastic Processes and an Introduction to Mathematical Finance

Автор: Chung K. L., AitSahlia Farid
Название: Elementary Probability Theory / With Stochastic Processes and an Introduction to Mathematical Finance
ISBN: 038795578X ISBN-13(EAN): 9780387955780
Издательство: Springer
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Цена: 69870.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Provides an introduction to probability theory and its applications.

An Introduction to Statistics: Second Edition

Автор: Carlson K & Winquist J
Название: An Introduction to Statistics: Second Edition
ISBN: 148337873X ISBN-13(EAN): 9781483378732
Издательство: Sage Publications
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Цена: 78150.00 T
Наличие на складе: Поставка под заказ.
Описание: The authors encourage an active approach to learning statistics through many in-depth activities that give students the opportunity to test or demonstrate their understanding of statistical concepts. The Second Edition is based on contemporary research on memory and the “testing effect” which requires students to answer questions to facilitate their long-term retention.

An Introduction to Game Theory

Автор: Osborne
Название: An Introduction to Game Theory
ISBN: 0195322487 ISBN-13(EAN): 9780195322484
Издательство: Oxford Academ
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Цена: 220690.00 T
Наличие на складе: Поставка под заказ.
Описание: Game-theoretic reasoning pervades economic theory and is used widely in other social and behavioural sciences. An Introduction to Game Theory International Edition, by Martin J. Osborne, presents the main principles of game theory and shows how they can be used to understand economics, social, political, and biological phenomena. The book introduces in an accessible manner the main ideas behind the theory rather than their mathematical expression. All concepts are defined precisely, and logical reasoning is used throughout. The book requires an understanding of basic mathematics but assumes no specific knowledge of economics, political science, or other social or behavioural sciences. Coverage includes the fundamental concepts of strategic games, extensive games with perfect information, and coalitional games; the more advanced subjects of Bayesian games and extensive games with imperfect information; and the topics of repeated games, bargaining theory, evolutionary equilibrium, rationalizability, and maxminimization. The book offers a wide variety of illustrations from the social and behavioural sciences. Each topic features examples that highlight theoretical points and illustrations that demonstrate how the theory may be used.

Introduction to Scientific Computing and Data Analysis

Автор: Holmes
Название: Introduction to Scientific Computing and Data Analysis
ISBN: 331930254X ISBN-13(EAN): 9783319302546
Издательство: Springer
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Цена: 74530.00 T
Наличие на складе: Невозможна поставка.
Описание: This textbook provides and introduction to numerical computing and its applications in science and engineering. The essential role of the mathematical theory underlying the methods is also considered, both for understanding how the method works, as well as how the error in the computation depends on the method being used.

Introduction to Probability, Second Edition

Автор: Joseph K. Blitzstein, Jessica Hwang
Название: Introduction to Probability, Second Edition
ISBN: 1138369918 ISBN-13(EAN): 9781138369917
Издательство: Taylor&Francis
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Цена: 74510.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Assumes one-semester of calculus. "Stories" make distributions (Normal, Binomial, Poisson that are widely-used in statistics) easier to remember, understand. Many books write down formulas without explaining clearly why these particular distributions are important or how they are all connected.

An Introduction to Statistical Learning

Автор: James Gareth
Название: An Introduction to Statistical Learning
ISBN: 1461471370 ISBN-13(EAN): 9781461471370
Издательство: Springer
Рейтинг:
Цена: 60550.00 T
Наличие на складе: Невозможна поставка.
Описание: This book presents key modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, and clustering.

Introduction to Mathematical Portfolio Theory

Автор: Joshi
Название: Introduction to Mathematical Portfolio Theory
ISBN: 1107042313 ISBN-13(EAN): 9781107042315
Издательство: Cambridge Academ
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Цена: 60190.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A concise yet comprehensive guide to the mathematics of portfolio theory from a modelling perspective, with discussion of the assumptions, limitations and implementations of the models as well as the theory underlying them. Aimed at advanced undergraduates, this book can be used for self-study or as a course text.

An Introduction to Quantitative Finance

Автор: Blyth Stephen
Название: An Introduction to Quantitative Finance
ISBN: 0199666598 ISBN-13(EAN): 9780199666591
Издательство: Oxford Academ
Рейтинг:
Цена: 45400.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The quantitative nature of complex financial transactions makes them a fascinating subject area for mathematicians of all types. This book gives an insight into financial engineering while building on introductory probability courses by detailing one of the most fascinating applications of the subject.

An Introduction to the Bootstrap

Автор: Efron
Название: An Introduction to the Bootstrap
ISBN: 0412042312 ISBN-13(EAN): 9780412042317
Издательство: Taylor&Francis
Рейтинг:
Цена: 153120.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An exploration of the many different bootstrap techniques. It discusses useful statistical techniques through real data examples and covers nonparametric regression, density estimation, classification trees, and least median squares regression. There are numerous exercises.

Introduction to random matrices

Автор: Anderson, Greg W. Guionnet, Alice Zeitouni, Ofer
Название: Introduction to random matrices
ISBN: 0521194520 ISBN-13(EAN): 9780521194525
Издательство: Cambridge Academ
Рейтинг:
Цена: 73920.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The theory of random matrices plays an important role in many areas of pure mathematics. This rigorous introduction is specifically designed for graduate students in mathematics or related sciences, who have a background in probability theory but have not been exposed to advanced notions of functional analysis, algebra or geometry.

Introduction to the New Statistics

Автор: Cumming, Geoff.
Название: Introduction to the New Statistics
ISBN: 1138825522 ISBN-13(EAN): 9781138825529
Издательство: Taylor&Francis
Рейтинг:
Цена: 66340.00 T
Наличие на складе: Нет в наличии.
Описание: This is the first introductory statistics text to use an estimation approach from the start to help readers understand effect sizes, confidence intervals (CIs), and meta-analysis (‘the new statistics’). It is also the first text to explain the new and exciting Open Science practices, which encourage replication and enhance the trustworthiness of research. In addition, the book explains NHST fully so students can understand published research. Numerous real research examples are used throughout. The book uses today’s most effective learning strategies and promotes critical thinking, comprehension, and retention, to deepen users’ understanding of statistics and modern research methods. The free ESCI (Exploratory Software for Confidence Intervals) software makes concepts visually vivid, and provides calculation and graphing facilities. The book can be used with or without ESCI. Other highlights include: - Coverage of both estimation and NHST approaches, and how to easily translate between the two. - Some exercises use ESCI to analyze data and create graphs including CIs, for best understanding of estimation methods. -Videos of the authors describing key concepts and demonstrating use of ESCI provide an engaging learning tool for traditional or flipped classrooms. -In-chapter exercises and quizzes with related commentary allow students to learn by doing, and to monitor their progress. -End-of-chapter exercises and commentary, many using real data, give practice for using the new statistics to analyze data, as well as for applying research judgment in realistic contexts. -Don’t fool yourself tips help students avoid common errors. -Red Flags highlight the meaning of "significance" and what p values actually mean. -Chapter outlines, defined key terms, sidebars of key points, and summarized take-home messages provide a study tool at exam time. -http://www.routledge.com/cw/cumming offers for students: ESCI downloads; data sets; key term flashcards; tips for using SPSS for analyzing data; and videos. For instructors it offers: tips for teaching the new statistics and Open Science; additional homework exercises; assessment items; answer keys for homework and assessment items; and downloadable text images; and PowerPoint lecture slides. Intended for introduction to statistics, data analysis, or quantitative methods courses in psychology, education, and other social and health sciences, researchers interested in understanding the new statistics will also appreciate this book. No familiarity with introductory statistics is assumed.


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