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 provides breadth and depth of coverage of pattern recognition theory and application, including modern topics like non-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.
Key Features
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 provides breadth and depth of coverage of pattern recognition theory and application, including modern topics like non-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.
Electronic engineering, computer science, computer engineering, biomedical engineering and applied mathematics students taking graduate courses on pattern recognition and machine learning. R&D engineers and university researchers in image and signal processing/analyisis, and computer vision.
