Statistical pattern recognition

Front Cover
Statistical pattern recognition is a very active area of study and research, which has seen many advances in recent years. New and emerging applications - such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition - require robust and efficient pattern recognition techniques. Statistical decision making and estimation are regarded as fundamental to the study of pattern recognition.


Statistical Pattern Recognition, Second Edition has been fully updated with new methods, applications and references. It provides a comprehensive introduction to this vibrant area - with material drawn from engineering, statistics, computer science and the social sciences - and covers many application areas, such as database design, artificial neural networks, and decision support systems.


* Provides a self-contained introduction to statistical pattern recognition.
* Each technique described is illustrated by real examples.
* Covers Bayesian methods, neural networks, support vector machines, and unsupervised classification.
* Each section concludes with a description of the applications that have been addressed and with further developments of the theory.
* Includes background material on dissimilarity, parameter estimation, data, linear algebra and probability.
* Features a variety of exercises, from 'open-book' questions to more lengthy projects.


The book is aimed primarily at senior undergraduate and graduate students studying statistical pattern recognition, pattern processing, neural networks, and data mining, in both statistics and engineering departments. It is also an excellent source of reference for technical professionals working in advanced information development environments.

For further information on the techniques and applications discussed in this book please visit www.statistical-pattern-recognition.net

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Contents

Density estimation parametric
33
Density estimation nonparametric
81
Linear discriminant analysis
123
Copyright

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About the author (2002)

Nadine Smith is a faculty member in the Bioengineering Department and the Graduate Program in Acoustics at Pennsylvania State University. She also holds a visiting faculty position at the Leiden University Medical Center. She is a Senior Member of the IEEE, and of the American Institute of Ultrasound in Medicine where she is on both the Bioeffects and Technical Standards Committees. Her current research involves ultrasound transducer design, ultrasound imaging and therapeutic applications of ultrasound.

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