Pattern Recognition Ebook

Publication: Academic Press
 
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Language: English
Publication Date: November 2008
Pages: 961
File Size: 11199 Kbytes

Restrictions set by Publisher:
- Text-to-speech feature not available.
- Printing is permitted.
- You can copy text from file.
- Free application Adobe Digital Editions, Aldiko reader, or Bluefire reader required .
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  • Don't get caught unaware. Preview ebook and open the sample ebook on each of your intended devices before continuing.
  • You will need a Free 3rd-party application that can read the intermediate .acsm file you will receive as download. PDF/Epub format is downloaded automatically by the application thereafter. Please install the necessary software first on your intended device of use.
  • - Printing is permitted.
    - You can copy text from file.
  • Refund Policy
    Refunds are not allowed after the ebook is opened so please open the ebook directly on your intended device. Refund requests should be recieved within 7 days after download is made available. Of course, if you get an incorrect ebook ( different from what is mentioned in the title) or if the ebook doesn't open on the initial device, then we'll assist with fixing the issue or get you a refund if a timely fix isn't available.
  • Customer Service
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Language: English
Publication Date: November 2008
File Size: 26982 Kbytes

Restrictions set by Publisher:
- Text-to-speech feature not available.
- Printing is permitted.
- You can copy text from file.
- Free application Adobe Digital Editions, Aldiko reader, or Bluefire reader required .
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ISBN: 9780080949123   Should I buy this Ebook?   Write a Review

Description

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.

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Pattern Recognition