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Algorithms of Estimation for Nonlinear Systems, Rafael Mart?nez-Guerra; Christopher Diego Cruz-Anc


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Автор: Rafael Mart?nez-Guerra; Christopher Diego Cruz-Anc
Название:  Algorithms of Estimation for Nonlinear Systems
ISBN: 9783319530390
Издательство: Springer
Классификация:






ISBN-10: 3319530399
Обложка/Формат: Hardcover
Страницы: 197
Вес: 0.49 кг.
Дата издания: 18.04.2017
Серия: Understanding Complex Systems
Язык: English
Издание: 1st ed. 2017
Иллюстрации: 10 illustrations, color; 48 illustrations, black and white; xx, 197 p. 58 illus., 10 illus. in color.
Размер: 234 x 156 x 14
Читательская аудитория: Professional & vocational
Основная тема: Physics
Подзаголовок: A Differential and Algebraic Viewpoint
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание:

Preface.- Analysis of input-affine nonlinear processes.- Basic Definitions of Differential Algebras.- Algebraic Observability Condition for Nonlinear systems and External behaviour.- Generalized Observability Canonical Forms.- Observer Synthesis.- Tracking and Stabilization Problems.- Parametric and State Estimation.- Observer synthesis for a more general class of Nonlinear Systems.- A Separation Principle for Nonlinear Systems.- Some uncommon observers with interesting applications.- Appendix A Singularity Treatment.- Appendix B Some properties for Nonlinear Systems.




Algorithms in Bioinformatics

Автор: Sung
Название: Algorithms in Bioinformatics
ISBN: 1420070339 ISBN-13(EAN): 9781420070330
Издательство: Taylor&Francis
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Цена: 13779.00 р.
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Описание: Presents an introduction to the algorithmic techniques applied in bioinformatics. For each topic, this title details the biological motivation, defines the corresponding computational problems, and includes examples to illustrate each algorithm.

Photonics : linear and nonlinear interactions of laser light and matter

Автор: Menzel
Название: Photonics : linear and nonlinear interactions of laser light and matter
ISBN: 3540231609 ISBN-13(EAN): 9783540231608
Издательство: Springer
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Цена: 18167.00 р.
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Описание: The definition of "photonics" has been broadened in recent years to include nonlinear and quantum optics, today usually based on laser light. This book covers the fundamental properties of photon and light beams, both experimentally and theoretically. It covers the essentials of linear interactions and most of the nonlinear interactions between light and matter in both the transparent and absorbing cases. It also provides a basic knowledge of modern lasers, as well as the principles of nonlinear optical spectroscopy. It is self-consistent and enriched by a large number of calculated illustrations, examples, and descriptive tables. Graduate students in physics and electrical engineering, as well as other sciences, will find this book a thorough introduction to the field, while for lecturers and scientists it offers a rich source of useful information and a ready-to-hand reference. About 4000 references open access to original literature.The second edition is completely revised and enlarged. 

Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies

Автор: Kelleher John D., Macnamee Brian, D`Arcy Aoife
Название: Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies
ISBN: 0262029448 ISBN-13(EAN): 9780262029445
Издательство: MIT Press
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Цена: 13543.00 р.
Наличие на складе: Нет в наличии.

Описание:

A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.

Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context.

After discussing the trajectory from data to insight to decision, the book describes four approaches to machine learning: information-based learning, similarity-based learning, probability-based learning, and error-based learning. Each of these approaches is introduced by a nontechnical explanation of the underlying concept, followed by mathematical models and algorithms illustrated by detailed worked examples. Finally, the book considers techniques for evaluating prediction models and offers two case studies that describe specific data analytics projects through each phase of development, from formulating the business problem to implementation of the analytics solution. The book, informed by the authors' many years of teaching machine learning, and working on predictive data analytics projects, is suitable for use by undergraduates in computer science, engineering, mathematics, or statistics; by graduate students in disciplines with applications for predictive data analytics; and as a reference for professionals.

Algorithms and Programs of Dynamic Mixture Estimation

Автор: Ivan Nagy; Evgenia Suzdaleva
Название: Algorithms and Programs of Dynamic Mixture Estimation
ISBN: 3319646702 ISBN-13(EAN): 9783319646701
Издательство: Springer
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Цена: 7685.00 р.
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Описание: This book provides a general theoretical background for constructing the recursive Bayesian estimation algorithms for mixture models.

Nonlinear Oscillations, Dynamical Systems, and Bifurcations of Vector Fields

Автор: Guckenheimer John, Holmes Philip
Название: Nonlinear Oscillations, Dynamical Systems, and Bifurcations of Vector Fields
ISBN: 0387908196 ISBN-13(EAN): 9780387908199
Издательство: Springer
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Цена: 18167.00 р.
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Описание: From the reviews: "This book is concerned with the application of methods from dynamical systems and bifurcation theories to the study of nonlinear oscillations. Chapter 1 provides a review of basic results in the theory of dynamical systems, covering both ordinary differential equations and discrete mappings. Chapter 2 presents 4 examples from nonlinear oscillations. Chapter 3 contains a discussion of the methods of local bifurcation theory for flows and maps, including center manifolds and normal forms. Chapter 4 develops analytical methods of averaging and perturbation theory. Close analysis of geometrically defined two-dimensional maps with complicated invariant sets is discussed in chapter 5. Chapter 6 covers global homoclinic and heteroclinic bifurcations. The final chapter shows how the global bifurcations reappear in degenerate local bifurcations and ends with several more models of physical problems which display these behaviors." #Book Review - Engineering Societies Library, New York#1 "An attempt to make research tools concerning `strange attractors' developed in the last 20 years available to applied scientists and to make clear to research mathematicians the needs in applied works. Emphasis on geometric and topological solutions of differential equations. Applications mainly drawn from nonlinear oscillations." #American Mathematical Monthly#2

Averaging Methods in Nonlinear Dynamical Systems

Автор: Sanders J. A., Verhulst F., Murdock J.
Название: Averaging Methods in Nonlinear Dynamical Systems
ISBN: 0387489169 ISBN-13(EAN): 9780387489162
Издательство: Springer
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Цена: 16769.00 р.
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Описание: Perturbation theory and in particular normal form theory has shown strong growth during the last decades. So it is not surprising that the authors have presented an extensive revision of the first edition of the Averaging Methods in Nonlinear Dynamical Systems book. There are many changes, corrections and updates in chapters on Basic Material and Asymptotics, Averaging, and Attraction. Chapters on Periodic Averaging and Hyperbolicity, Classical (first level) Normal Form Theory, Nilpotent (classical) Normal Form, and Higher Level Normal Form Theory are entirely new and represent new insights in averaging, in particular its relation with dynamical systems and the theory of normal forms. Also new are surveys on invariant manifolds in Appendix C and averaging for PDEs in Appendix E. Since the first edition, the book has expanded in length and the third author, James Murdock has been added.Review of First Edition"One of the most striking features of the book is the nice collection of examples, which range from the very simple to some that are elaborate, realistic, and of considerable practical importance. Most of them are presented in careful detail and are illustrated with profuse, illuminating diagrams." - Mathematical Reviews

Conditional Moment Estimation of Nonlinear Equation Systems

Автор: Joachim Inkmann
Название: Conditional Moment Estimation of Nonlinear Equation Systems
ISBN: 3540412077 ISBN-13(EAN): 9783540412076
Издательство: Springer
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Цена: 11179.00 р.
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Описание: Generalized method of moments (GMM) estimation of nonlinear systems has two important advantages over conventional maximum likelihood (ML) estimation: GMM estimation usually requires less restrictive distributional assumptions and remains computationally attractive when ML estimation becomes burdensome or even impossible.

Control and Estimation of Distributed Parameter Systems: Nonlinear Phenomena

Автор: Wolfgang Desch; Franz Kappel; Karl Kunisch
Название: Control and Estimation of Distributed Parameter Systems: Nonlinear Phenomena
ISBN: 3034896662 ISBN-13(EAN): 9783034896665
Издательство: Springer
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Цена: 6986.00 р.
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Описание: 22 papers on control of nonlinear partial differential equations highlight the area from a broad variety of viewpoints. A significant part of the volume is devoted to applications in engineering, continuum mechanics and population biology.

Neural Network-Based State Estimation of Nonlinear Systems

Автор: Heidar A. Talebi; Farzaneh Abdollahi; Rajni V. Pat
Название: Neural Network-Based State Estimation of Nonlinear Systems
ISBN: 1441914374 ISBN-13(EAN): 9781441914378
Издательство: Springer
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Цена: 15672.00 р.
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Описание: This text offers neural network schemes for state estimation, system identification and fault detection. It covers mathematical proof of stability, experimental evaluation, and robustness against unmolded dynamics, external disturbances and measurement noises.

Algorithms, Complexity Analysis and VLSI Architectures for MPEG-4 Motion Estimation

Автор: Peter M. Kuhn
Название: Algorithms, Complexity Analysis and VLSI Architectures for MPEG-4 Motion Estimation
ISBN: 1441950885 ISBN-13(EAN): 9781441950888
Издательство: Springer
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Цена: 19564.00 р.
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Motion Estimation Algorithms for Video Compression

Автор: Borko Furht; Joshua Greenberg; Raymond Westwater
Название: Motion Estimation Algorithms for Video Compression
ISBN: 146137863X ISBN-13(EAN): 9781461378631
Издательство: Springer
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Цена: 27950.00 р.
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Описание: Then, we give a survey of current motion estimation search algorithms, including the exhaustive search and a number of fast search algorithms. The complexity of the DCUPS algorithm is comparable to other popular motion estimation techniques, however the algorithm shows superior results in terms of compression ratios and video qUality.

Algorithms for Obstetrics and Gynaecology

Автор: Mukhopadhyay Sambit, Morris Edward, Arulkumaran Sa
Название: Algorithms for Obstetrics and Gynaecology
ISBN: 0199651396 ISBN-13(EAN): 9780199651399
Издательство: Oxford Academ
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Цена: 7760.00 р.
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Описание: Algorithms in Obstetrics and Gynaecology presents the core knowledge needed to tackle all situations in obstetrics and gynaecology, in a structured fashion. All algorithms are designed to support rapid decision making in the most clinically relevant situations to minimise the risks of a poor outcome.


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