Pattern Recognition, 4th Edition
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
- 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).
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