Nonlinear Estimation and Classification
Author | : David D. Denison |
Publisher | : |
Total Pages | : 488 |
Release | : 2014-01-15 |
Genre | : |
ISBN | : 9781489905123 |
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Author | : David D. Denison |
Publisher | : |
Total Pages | : 488 |
Release | : 2014-01-15 |
Genre | : |
ISBN | : 9781489905123 |
Author | : David D. Denison |
Publisher | : Springer Science & Business Media |
Total Pages | : 465 |
Release | : 2013-11-11 |
Genre | : Mathematics |
ISBN | : 0387215794 |
Researchers in many disciplines face the formidable task of analyzing massive amounts of high-dimensional and highly-structured data. This is due in part to recent advances in data collection and computing technologies. As a result, fundamental statistical research is being undertaken in a variety of different fields. Driven by the complexity of these new problems, and fueled by the explosion of available computer power, highly adaptive, non-linear procedures are now essential components of modern "data analysis," a term that we liberally interpret to include speech and pattern recognition, classification, data compression and signal processing. The development of new, flexible methods combines advances from many sources, including approximation theory, numerical analysis, machine learning, signal processing and statistics. The proposed workshop intends to bring together eminent experts from these fields in order to exchange ideas and forge directions for the future.
Author | : David G. T. Denison |
Publisher | : John Wiley & Sons |
Total Pages | : 302 |
Release | : 2002-05-06 |
Genre | : Mathematics |
ISBN | : 9780471490364 |
Bei der Regressionsanalyse von Datenmaterial erhält man leider selten lineare oder andere einfache Zusammenhänge (parametrische Modelle). Dieses Buch hilft Ihnen, auch komplexere, nichtparametrische Modelle zu verstehen und zu beherrschen. Stärken und Schwächen jedes einzelnen Modells werden durch die Anwendung auf Standarddatensätze demonstriert. Verbreitete nichtparametrische Modelle werden mit Hilfe von Bayes-Verfahren in einen kohärenten wahrscheinlichkeitstheoretischen Zusammenhang gebracht.
Author | : Ferdinand van der Heijden |
Publisher | : John Wiley & Sons |
Total Pages | : 440 |
Release | : 2005-06-10 |
Genre | : Science |
ISBN | : 0470090146 |
Classification, Parameter Estimation and State Estimation is a practical guide for data analysts and designers of measurement systems and postgraduates students that are interested in advanced measurement systems using MATLAB. 'Prtools' is a powerful MATLAB toolbox for pattern recognition and is written and owned by one of the co-authors, B. Duin of the Delft University of Technology. After an introductory chapter, the book provides the theoretical construction for classification, estimation and state estimation. The book also deals with the skills required to bring the theoretical concepts to practical systems, and how to evaluate these systems. Together with the many examples in the chapters, the book is accompanied by a MATLAB toolbox for pattern recognition and classification. The appendix provides the necessary documentation for this toolbox as well as an overview of the most useful functions from these toolboxes. With its integrated and unified approach to classification, parameter estimation and state estimation, this book is a suitable practical supplement in existing university courses in pattern classification, optimal estimation and data analysis. Covers all contemporary main methods for classification and estimation. Integrated approach to classification, parameter estimation and state estimation Highlights the practical deployment of theoretical issues. Provides a concise and practical approach supported by MATLAB toolbox. Offers exercises at the end of each chapter and numerous worked out examples. PRtools toolbox (MATLAB) and code of worked out examples available from the internet Many examples showing implementations in MATLAB Enables students to practice their skills using a MATLAB environment
Author | : Johan A.K. Suykens |
Publisher | : Springer Science & Business Media |
Total Pages | : 265 |
Release | : 2012-12-06 |
Genre | : Technology & Engineering |
ISBN | : 1461557038 |
Nonlinear Modeling: Advanced Black-Box Techniques discusses methods on Neural nets and related model structures for nonlinear system identification; Enhanced multi-stream Kalman filter training for recurrent networks; The support vector method of function estimation; Parametric density estimation for the classification of acoustic feature vectors in speech recognition; Wavelet-based modeling of nonlinear systems; Nonlinear identification based on fuzzy models; Statistical learning in control and matrix theory; Nonlinear time-series analysis. It also contains the results of the K.U. Leuven time series prediction competition, held within the framework of an international workshop at the K.U. Leuven, Belgium in July 1998.
Author | : Liming Dai |
Publisher | : Springer |
Total Pages | : 456 |
Release | : 2018-01-29 |
Genre | : Technology & Engineering |
ISBN | : 3319694804 |
This book analyzes the updated principles and applications of nonlinear approaches to solve engineering and physics problems. The knowledge on nonlinearity and the comprehension of nonlinear approaches are inevitable to future engineers and scientists, making this an ideal book for engineers, engineering students, and researchers in engineering, physics, and mathematics. Chapters are of specific interest to readers who seek expertise in optimization, nonlinear analysis, mathematical modeling of complex forms, and non-classical engineering problems. The book covers methodologies and applications from diverse areas such as vehicle dynamics, surgery simulation, path planning, mobile robots, contact and scratch analysis at the micro and nano scale, sub-structuring techniques, ballistic projectiles, and many more.
Author | : László Györfi |
Publisher | : Springer Science & Business Media |
Total Pages | : 662 |
Release | : 2006-04-18 |
Genre | : Mathematics |
ISBN | : 0387224424 |
This book provides a systematic in-depth analysis of nonparametric regression with random design. It covers almost all known estimates. The emphasis is on distribution-free properties of the estimates.
Author | : Antonio Criminisi |
Publisher | : Foundations and Trends(r) in C |
Total Pages | : 162 |
Release | : 2012-03 |
Genre | : Computers |
ISBN | : 9781601985408 |
Presents a unified, efficient model of random decision forests which can be used in a number of applications such as scene recognition from photographs, object recognition in images, automatic diagnosis from radiological scans and document analysis.
Author | : Sneh Gulati |
Publisher | : Springer Science & Business Media |
Total Pages | : 132 |
Release | : 2003-01-27 |
Genre | : Mathematics |
ISBN | : 9780387001388 |
By providing a comprehensive look at statistical inference from record-breaking data in both parametric and nonparametric settings, this book treats the area of nonparametric function estimation from such data in detail. Its main purpose is to fill this void on general inference from record values. Statisticians, mathematicians, and engineers will find the book useful as a research reference. It can also serve as part of a graduate-level statistics or mathematics course.
Author | : Geoffrey I. Webb |
Publisher | : Springer Science & Business Media |
Total Pages | : 1293 |
Release | : 2004-11-29 |
Genre | : Computers |
ISBN | : 3540240594 |
This book constitutes the refereed proceedings of the 17th Australian Conference on Artificial Intelligence, AI 2004, held in Cairns, Australia, in December 2004. The 78 revised full papers and 62 revised short papers presented were carefully reviewed and selected from 340 submissions. The papers are organized in topical sections on agents; biomedical applications; computer vision, image processing, and pattern recognition; ontologies, knowledge discovery and data mining; natural language and speech processing; problem solving and reasoning; robotics; and soft computing.