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Machine Learning for Signal Processing, Little Max A



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Автор: Little Max A   (Макс А. Литтл)
Название:  Machine Learning for Signal Processing
Перевод названия: Макс А. Литтл: Машинное обучение для обработки сигналов
ISBN: 9780198714934
Издательство: Oxford Academ
Классификация:
ISBN-10: 0198714939
Обложка/Формат: Hardcover
Страницы: 384
Вес: 0.381 кг.
Дата издания: 13.08.2019
Язык: English
Иллюстрации: 77 grayscale and 52 color line figures, 1 color halftone
Размер: 196 x 252 x 25
Читательская аудитория: General (us: trade)
Подзаголовок: Data science, algorithms, and computational statistics
Ссылка на Издательство: Link
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Поставляется из: Англии



The theory of quantum information

Автор: Watrous, John (university Of Waterloo, Ontario)
Название: The theory of quantum information
ISBN: 1107180562 ISBN-13(EAN): 9781107180567
Издательство: Cambridge Academ
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Цена: 11387 р.
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Описание: This largely self-contained book on the theory of quantum information focuses on precise mathematical formulations and proofs of fundamental facts that form the foundation of the subject. It is intended for graduate students and researchers in mathematics, computer science, and theoretical physics seeking to develop a thorough understanding of key results, proof techniques, and methodologies that are relevant to a wide range of research topics within the theory of quantum information and computation. The book is accessible to readers with an understanding of basic mathematics, including linear algebra, mathematical analysis, and probability theory. An introductory chapter summarizes these necessary mathematical prerequisites, and starting from this foundation, the book includes clear and complete proofs of all results it presents. Each subsequent chapter includes challenging exercises intended to help readers to develop their own skills for discovering proofs concerning the theory of quantum information.

Pattern Recognition and Machine Learning

Автор: Christopher M. Bishop
Название: Pattern Recognition and Machine Learning
ISBN: 0387310738 ISBN-13(EAN): 9780387310732
Издательство: Springer
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Цена: 12621 р.
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Описание: The dramatic growth in practical applications for machine learning over the last ten years has been accompanied by many important developments in the underlying algorithms and techniques. For example, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic techniques. The practical applicability of Bayesian methods has been greatly enhanced by the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation, while new models based on kernels have had a significant impact on both algorithms and applications.A forthcoming companion volume will deal with practical aspects of pattern recognition and machine learning, and will include free software implementations of the key algorithms along with example data sets and demonstration programs.Christopher Bishop is Assistant Director at Microsoft Research Cambridge, and also holds a Chair in Computer Science at the University of Edinburgh. He is a Fellow of Darwin College Cambridge, and was recently elected Fellow of the Royal Academy of Engineering. The author's previous textbook "Neural Networks for Pattern Recognition" has been widely adopted.Coming soon:*For students, worked solutions to a subset of exercises available on a public web site (for exercises marked "www" in the text)*For instructors, worked solutions to remaining exercises from the Springer web site*Lecture slides to accompany each chapter*Data sets available for download

Machine Learning

Автор: Kevin Murphy
Название: Machine Learning
ISBN: 0262018020 ISBN-13(EAN): 9780262018029
Издательство: MIT Press
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Цена: 14462 р.
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Описание:

A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.

Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.

The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package -- PMTK (probabilistic modeling toolkit) -- that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

Digital Signal Processing Using MATLAB

Автор: Schilling Robert J
Название: Digital Signal Processing Using MATLAB
ISBN: 1305636600 ISBN-13(EAN): 9781305636606
Издательство: Cengage Learning
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Цена: 13574 р.
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Описание: Focus on the development, implementation, and application of modern DSP techniques with DIGITAL SIGNAL PROCESSING USING MATLAB (R), 3E. Written in an engaging, informal style, this edition immediately captures your attention and encourages you to explore each critical topic. Every chapter starts with a motivational section that highlights practical examples and challenges that you can solve using techniques covered in the chapter.

Each chapter concludes with a detailed case study example, a chapter summary with learning outcomes, and practical homework problems cross-referenced to specific chapter sections for your convenience. DSP Companion software accompanies each book to enable further investigation. The DSP Companion software operates with MATLAB (R) and provides intriguing demonstrations as well as interactive explorations of analysis and design concepts.

Data Mining. Practical Machine Learning Tools and Techniques, 4 ed.

Автор: Witten, Ian H.
Название: Data Mining. Practical Machine Learning Tools and Techniques, 4 ed.
ISBN: 0128042915 ISBN-13(EAN): 9780128042915
Издательство: Elsevier Science
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Цена: 8754 р.
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Описание: Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches. Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research. Please visit the book companion website at http://www.cs.waikato.ac.nz/ml/weka/book.html. It contains. . . Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book. Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book. Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc. . .

Sound Capture for Human / Machine Interfaces / Practical Aspects of Microphone Array Signal Processing

Автор: Herbordt Wolfgang
Название: Sound Capture for Human / Machine Interfaces / Practical Aspects of Microphone Array Signal Processing
ISBN: 3540239545 ISBN-13(EAN): 9783540239543
Издательство: Springer
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Цена: 16334 р.
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Описание: With a continuously increasing desire for natural and comfortable human/machine interaction, the acoustic interface of any terminal for multimedia or telecommunication services is challenged to allow seamless and hands-free audio communication. Sound Capture for Human-Machine Interfaces introduces the practical aspects of microphone array signal processing and presents various combinations of beamforming and acoustic echo cancellation.

Optimal Estimation of Parameters

Автор: Rissanen
Название: Optimal Estimation of Parameters
ISBN: 1107004748 ISBN-13(EAN): 9781107004740
Издательство: Cambridge Academ
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Цена: 17714 р.
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Описание: This book presents a comprehensive and consistent theory of estimation. The framework described leads naturally to a generalized maximum capacity estimator. This approach allows the optimal estimation of real-valued parameters, their number and intervals, as well as providing common ground for explaining the power of these estimators. Beginning with a review of coding and the key properties of information, the author goes on to discuss the techniques of estimation and develops the generalized maximum capacity estimator, based on a new form of Shannon's mutual information and channel capacity. Applications of this powerful technique in hypothesis testing and denoising are described in detail. Offering an original and thought-provoking perspective on estimation theory, Jorma Rissanen's book is of interest to graduate students and researchers in the fields of information theory, probability and statistics, econometrics and finance.

Machine Learning

Автор: Flach
Название: Machine Learning
ISBN: 1107422221 ISBN-13(EAN): 9781107422223
Издательство: Cambridge Academ
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Цена: 7771 р.
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Описание: As one of the most comprehensive machine learning texts around, this book does justice to the field's incredible richness, but without losing sight of the unifying principles. Peter Flach's clear, example-based approach begins by discussing how a spam filter works, which gives an immediate introduction to machine learning in action, with a minimum of technical fuss. Flach provides case studies of increasing complexity and variety with well-chosen examples and illustrations throughout. He covers a wide range of logical, geometric and statistical models and state-of-the-art topics such as matrix factorisation and ROC analysis. Particular attention is paid to the central role played by features. The use of established terminology is balanced with the introduction of new and useful concepts, and summaries of relevant background material are provided with pointers for revision if necessary. These features ensure Machine Learning will set a new standard as an introductory textbook.

Machine Learning

Автор: Flach
Название: Machine Learning
ISBN: 1107096391 ISBN-13(EAN): 9781107096394
Издательство: Cambridge Academ
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Цена: 16810 р.
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Описание: As one of the most comprehensive machine learning texts around, this book does justice to the field's incredible richness, but without losing sight of the unifying principles. Peter Flach's clear, example-based approach begins by discussing how a spam filter works, which gives an immediate introduction to machine learning in action, with a minimum of technical fuss. Flach provides case studies of increasing complexity and variety with well-chosen examples and illustrations throughout. He covers a wide range of logical, geometric and statistical models and state-of-the-art topics such as matrix factorisation and ROC analysis. Particular attention is paid to the central role played by features. The use of established terminology is balanced with the introduction of new and useful concepts, and summaries of relevant background material are provided with pointers for revision if necessary. These features ensure Machine Learning will set a new standard as an introductory textbook.

Kernel Methods and Machine Learning

Автор: Kung
Название: Kernel Methods and Machine Learning
ISBN: 110702496X ISBN-13(EAN): 9781107024960
Издательство: Cambridge Academ
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Цена: 14099 р.
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Описание: Offering a fundamental basis in kernel-based learning theory, this book covers both statistical and algebraic principles. It provides over 30 major theorems for kernel-based supervised and unsupervised learning models. The first of the theorems establishes a condition, arguably necessary and sufficient, for the kernelization of learning models. In addition, several other theorems are devoted to proving mathematical equivalence between seemingly unrelated models. With over 25 closed-form and iterative algorithms, the book provides a step-by-step guide to algorithmic procedures and analysing which factors to consider in tackling a given problem, enabling readers to improve specifically designed learning algorithms, build models for new applications and develop efficient techniques suitable for green machine learning technologies. Numerous real-world examples and over 200 problems, several of which are Matlab-based simulation exercises, make this an essential resource for graduate students and professionals in computer science, electrical and biomedical engineering. Solutions to problems are provided online for instructors.

Financial Signal Processing and Machine Learning

Автор: Ali N. Akansu, Sanjeev R. Kulkarni, Dmitry M. Malioutov
Название: Financial Signal Processing and Machine Learning
ISBN: 1118745671 ISBN-13(EAN): 9781118745670
Издательство: Wiley
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Цена: 14838 р.
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Описание: The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in

Human and Machine Hearing

Автор: Lyon
Название: Human and Machine Hearing
ISBN: 1107007534 ISBN-13(EAN): 9781107007536
Издательство: Cambridge Academ
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Цена: 10483 р.
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Описание: Human and Machine Hearing is the first book to comprehensively describe how human hearing works and how to build machines to analyze sounds in the same way that people do. Drawing on over thirty-five years of experience in analyzing hearing and building systems, Richard F. Lyon explains how we can now build machines with close-to-human abilities in speech, music, and other sound-understanding domains. He explains human hearing in terms of engineering concepts, and describes how to incorporate those concepts into machines for a wide range of modern applications. The details of this approach are presented at an accessible level, to bring a diverse range of readers, from neuroscience to engineering, to a common technical understanding. The description of hearing as signal-processing algorithms is supported by corresponding open-source code, for which the book serves as motivating documentation.


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