Abstract
The present work gives an account of basic principles and available techniques for the analysis and design of pattern processing and recognition systems. Areas covered include decision functions, pattern classification by distance functions, pattern classification by likelihood functions, the perceptron and the potential function approaches to trainable pattern classifiers, statistical approach to trainable classifiers, pattern preprocessing and feature selection, and syntactic pattern recognition.
Keywords
Pattern recognition (psychology)Computer scienceArtificial intelligence
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Publication Info
- Year
- 2009
- Type
- book-chapter
- Pages
- 41-75
- Citations
- 3205
- Access
- Closed
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Cite This
Julius Τ. Tou,
R. C. Gonzalez
(2009).
Pattern Recognition Principles.
, 41-75.
https://doi.org/10.1201/9781420090741.ch2
Identifiers
- DOI
- 10.1201/9781420090741.ch2