Keith Copsey

 

 

 

 

 

 

 

 

Name: Keith Copsey

Job: Statistical Pattern Recognition and Data Mining Scientist

Interests: Football (Tranmere Rovers and England), Travelling

Current location: Great Malvern, Worcestershire, England

Email: kcopSPAMPROTECTIONDELETECAPITALSsey@gmail.com

Work: http://kcopsey.googlepages.com/work, (Contains copy of PhD thesis)

Statistical Pattern Recognition Book:

Webb, A.R. and Copsey, K.D., Statistical Pattern Recognition, Third Edition, John Wiley and Sons, Chichester, 2011.  

http://eu.wiley.com/WileyCDA/WileyTitle/productCd-0470682280.html 

http://www.amazon.co.uk/Statistical-Pattern-Recognition-Andrew-Webb/dp/0470682280

Outline:

Statistical pattern recognition concerns 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. Topics 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 and basic techniques for analysing the properties of datasets.
  • Introduces readers to methods for Bayesian density estimation and looks at new applications in biometrics and security.
  • 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 departments.  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.

Photos:

http://picasaweb.google.com/kcopsey