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Pattern Recognition & Matlab Intro

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Sergios Theodoridis 作者
Academic Press
譯者
2010-4-16 出版日期
500 頁數
USD 124.00 價格
Hardcover
叢書系列
9780123744913 圖書編碼

Pattern Recognition & Matlab Intro 在線電子書 圖書標籤: 機器學習   


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Pattern Recognition & Matlab Intro 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

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Pattern Recognition & Matlab Intro 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024



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Pattern Recognition & Matlab Intro 在線電子書 pdf 下載 txt下載 epub 下載 mobi 在線電子書下載

Pattern Recognition & Matlab Intro 在線電子書 圖書描述

This book considers classical and current 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 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.

This edition includes many more worked examples and diagrams (in two colour) to help give greater understanding of the methods and their application. Computer-based problems will be included with MATLAB code. The accompanying book contains extra worked examples and MATLAB code of all the examples used in this book.

This specially priced set includes a copy of Theodoridis/Koutroumbas, Pattern Recognition 4e and Theodoridis/Pikrakis/Koutroumbas/Cavouras, Introduction to Pattern Recognition: A Matlab Approach. The main text providesbreadth and depth ofcoverage of pattern recognition theory and application,including modern topics likenon-linear dimensionality reduction techniques, relevance feedback, semi-supervised learning, spectral clustering, and combining clustering algorithms. Together with worked examples, exercises, and Matlab applications it provides the most comprehensive coverage currently available. The accompanying manual includes MATLAB code of the most common methods and algorithms in the book, together with a descriptive summary and solved problems, and including real-life data sets in imaging and audio recognition.

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