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速递书局
封面: |
|
题名: |
Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB |
作者: |
Ferdinand van der Heijden, Robert Duin |
出版社: |
John Wiley & Sons Ltd |
出版日期: |
2004年9月24日 |
ISBN: |
0470090138 |
附属页: |
齐全 |
书签: |
无 |
格式: |
清晰PDF |
内容简介: |
"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.This book: covers all contemporary main methods for classification and estimation; takes an 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; and, offers exercises at the end of each chapter and numerous worked out examples. PRtools toolbox (MATLAB) and code of worked out examples are available from the internet. It also includes many examples showing implementations in MATLAB. This book enables students to practice their skills using a MATLAB environment. |
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