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Pattern recognition : and, Introduction to pattern recognition : a MATLAB approach 🔍
Koutroumbas, Konstantinos, Theodoridis, Sergios, Sergios Theodoridis, Konstantinos Koutroumbas Elsevier Inc., 2009, 2009
英语 [en] · PDF · 234.4MB · 2009 · 📗 未知类型的图书 · 🚀/duxiu/zlibzh · Save
描述
This book considers classical and current theory and practice, of supervised, unsupervised and semi-supervised pattern recognition, to build a complete background for professionals and students of engineering. The authors, leading experts in the field of pattern recognition, have provided an up-to-date, self-contained volume encapsulating this wide spectrum of information. The very latest methods are incorporated in this edition: semi-supervised learning, combining clustering algorithms, and relevance feedback.
· Thoroughly developed to include many more worked examples to give greater understanding of the various methods and techniques
· Many more diagrams included--now in two color--to provide greater insight through visual presentation
· Matlab code of the most common methods are given at the end of each chapter.
· More Matlab code is available, together with an accompanying manual, via this site
· Latest hot topics included to further the reference value of the text including non-linear dimensionality reduction techniques, relevance feedback, semi-supervised learning, spectral clustering, combining clustering algorithms.
· An accompanying book with Matlab code of the most common methods and algorithms in the book, together with a descriptive summary, and solved examples including real-life data sets in imaging, and audio recognition. The companion book will be available separately or at a special packaged price (ISBN: 9780123744869).
Thoroughly developed to include many more worked examples to give greater understanding of the various methods and techniques Many more diagrams included--now in two color--to provide greater insight through visual presentation Matlab code of the most common methods are given at the end of each chapter An accompanying book with Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition. The companion book is available separately or at a special packaged price (Book ISBN: 9780123744869. Package ISBN: 9780123744913) Latest hot topics included to further the reference value of the text including non-linear dimensionality reduction techniques, relevance feedback, semi-supervised learning, spectral clustering, combining clustering algorithms Solutions manual, powerpoint slides, and additional resources are available to faculty using the text for their course. Register at www.textbooks.elsevier.com and search on "Theodoridis" to access resources for instructor.
备用文件名
zlibzh/no-category/Koutroumbas, Konstantinos, Theodoridis, Sergios, Sergios Theodoridis, Konstantinos Koutroumbas/40360657_116691059.pdf
备选标题
Pattern Recognition [With Introduction to Pattern Recognition] - 4th Edition
备选标题
Matlab Introduction to Pattern Recognition
备选标题
Pattern recognition ; MATLAB introduction
备选标题
Pattern recognition = Mo shi shi bie
备选标题
Pattern Recognition Fourth Edition
备选标题
模式识别 英文版 第4版
备选标题
40360657
备选作者
Theodoridis, Sergios, Pikrakis, Aggelos, Koutroumbas, Konstantinos, Cavouras, Dionisis
备选作者
Sergios Theodoridis; Aggelos Pikrakis; Konstantinos Koutroumbas; Dionisis Cavouras
备选作者
(希)Sergios Theodoridis, (希)Konstantinos Koutroumbas著; Eodoridis Th; Utroumbas Ko
备选作者
Konstantinos Koutroumbas; Sergios Theodoridis
备选作者
Sergios Theodoridis ... [et al.]
备选作者
(希)西奥多里德斯等著
备用出版商
Academic Press, Incorporated
备用出版商
Elsevier (Singapore) Pte Ltd
备用出版商
Morgan Kaufmann Publishers
备用出版商
Elsevier/Academic Press
备用出版商
China Machine Press
备用出版商
Syngress Publishing
备用出版商
Brooks/Cole
备用出版商
机械工业出版社
备用版本
Jing dian yuan ban shu ku, 4th ed., English photoprint ed, Beijing, China, 2009
备用版本
Jing dian yuan ban shu ku, Ying yin ban, Beijing, 2009
备用版本
4th ed., Amsterdam, London, Massachusetts, 2009
备用版本
United States, United States of America
备用版本
4th ed, Burlington, MA ; London, ©2009
备用版本
Elsevier Ltd., Burlington, MA, 2009
备用版本
Elsevier Ltd., Burlington, MA, 2010
备用版本
Burlington, MA, Massachusetts, 2010
备用版本
China, People's Republic, China
备用版本
Fourth Edition, PT, 2008
备用版本
New ed, London, 2009
备用版本
Singapore, Singapore
备用版本
Amsterdam, ©2010
备用版本
London, ©2010
备用版本
1, PS, 2010
备用版本
4, 2008
元数据中的注释
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元数据中的注释
"Compliment of the book Pattern recognition, 4th edition, by S. Theodoridis and K. Koutroumbas, Academic Press, 2009."
Includes bibliographical references and index.
元数据中的注释
Previous ed.: Amsterdam: Academic, 2003.
Includes bibliographical references and index.
元数据中的注释
MiU
备用描述
Introduction to Pattern Recognition: A Matlab Approach is an accompanying manual to Theodoridis/Koutroumbas'Pattern Recognition. It includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition. This text is designed for electronic engineering, computer science, computer engineering, biomedical engineering and applied mathematics students taking graduate courses on pattern recognition and machine learning as well as R&D engineers and university researchers in image and signal processing/analyisis, and computer vision. Matlab code and descriptive summary of the most common methods and algorithms in Theodoridis/Koutroumbas, Pattern Recognition, Fourth Edition Solved examples in Matlab, including real-life data sets in imaging and audio recognition Available separately or at a special package price with the main text (ISBN for package: 978-0-12-374491-3)
备用描述
Introduction to Pattern A Matlab Approach is an accompanying manual to Theodoridis/Koutroumbas' Pattern Recognition. It includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition. This text is designed for electronic engineering, computer science, computer engineering, biomedical engineering and applied mathematics students taking graduate courses on pattern recognition and machine learning as well as R&D engineers and university researchers in image and signal processing/analyisis, and computer vision.
备用描述
An accompanying manual to Theodoridis/Koutroumbas, Pattern Recognition, that includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition.<br><br>*Matlab code and descriptive summary of the most common methods and algorithms in Theodoridis/Koutroumbas, Pattern Recognition 4e.<br>*Solved examples in Matlab, including real-life data sets in imaging and audio recognition<br>*Available separately or at a special package price with the main text (ISBN for package: 978-0-12-374491-3)
备用描述
"This book considers classical and current theory and practice of supervised, unsupervised and semi-supervised pattern recognition, to build a complete background for professionals and students of engineering. The authors have provided an up-to-date, self-contained volume encapsulating this wide spectrum of information. The very latest methods are incorporated in this edition including semi-supervised learning, non-linear dimensionality reduction techniques and spectral clustering."--Jacket
备用描述
This is an accompanying manual to "Theodoridis/Koutroumbas, Pattern Recognition", that includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition. It also includes Matlab code and descriptive summary of the most common methods and algorithms in "Theodoridis/Koutroumbas, Pattern Recognition 4e"
备用描述
Looks at the classical and the theory and practice, of both supervised and unsupervised pattern recognition, to build a complete background for professionals and students of engineering. The authors, leading experts in the field of pattern recognition, have provided a self-contained volume encapsulating this wide spectrum of information.
备用描述
Classifiers based on Bayes decision theory
Classifiers based on cost function optimization
Data transformation : feature generation and dimensionality reduction
Feature selection
Template matching
Hidden Markov models
Clustering
Appendix.
开源日期
2024-06-13
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