Statistical Pattern Recognition (ePub)

Statistical pattern recognition relates to the use of statistical
techniques for analysing data measurements in order to extract
information and make justified decisions. It is a very active
area of study and research, which has seen many advances in recent
years. Applications such as data mining, web searching, multimedia
data retrieval, face recognition, and cursive handwriting
recognition, all require robust and efficient pattern recognition
techniques.

This third edition provides an introduction to statistical
pattern theory and techniques, with material drawn from a wide
range of fields, including the areas of engineering, statistics,
computer science and the social sciences. The book has been updated
to cover new methods and applications, and includes a wide range of
techniques such as Bayesian methods, neural networks, support
vector machines, feature selection and feature reduction
techniques.Technical descriptions and motivations are provided, and
the techniques are illustrated using real examples.

Statistical Pattern Recognition, 3rd
Edition:

* Provides a self-contained introduction to statistical pattern
recognition.

* Includes new material presenting the analysis of complex
networks.

* Introduces readers to methods for Bayesian density
estimation.

* Presents descriptions of new applications in biometrics,
security, finance and condition monitoring.

* Provides descriptions and guidance for implementing techniques,
which will be invaluable to software engineers and developers
seeking to develop real applications

* Describes mathematically the range of statistical pattern
recognition techniques.

* Presents a variety of exercises including more extensive
computer projects.

The in-depth technical descriptions make the book suitable for
senior undergraduate and graduate students in statistics, computer
science and engineering. Statistical Pattern
Recognition is also an excellent reference source for technical
professionals. Chapters have been arranged to facilitate
implementation of the techniques by software engineers and
developers in non-statistical engineering fields.

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