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 applicationsDescribes 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.
www.wiley.com/go/statistical_pattern_recognition
Or split into 4x interest-free payments of 25% on orders over R50
Learn more
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 applicationsDescribes 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.
www.wiley.com/go/statistical_pattern_recognition
Imprint | John Wiley & Sons |
Country of origin | United States |
Release date | October 2011 |
Availability | Expected to ship within 12 - 17 working days |
First published | November 2011 |
Authors | A.R. Webb |
Dimensions | 248 x 177 x 41mm (L x W x T) |
Format | Hardcover |
Pages | 666 |
Edition | 3rd Edition |
ISBN-13 | 978-0-470-68227-2 |
Barcode | 9780470682272 |
Categories | |
LSN | 0-470-68227-2 |