Introduction to statistical pattern recognition / Keinosuke Fukunaga.
Material type:
Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds |
---|---|---|---|---|---|---|---|
![]() |
e-Library
Electronic Book@IST |
EBook | Available |
Includes bibliographical references and index.
Print version record.
Cover; Frontmatter; Chapter 1: Introduction; Chapter 2: Random Vectors and Their Properties; Chapter 3: Hypothesis Testing; Chapter 4: Parametric Classifiers; Chapter 5: Parameter Estimation; Chapter 6: Nonparametric Density Estimation; Chapter 7: Nonparametric Classification and Error Estimation; Chapter 8: Successive Parameter Estimation; Chapter 9: Feature Extraction and Linear Mapping for Signal Representation; Chapter 10: Feature Extraction and Linear Mapping for Classification; Chapter 11: Clustering; Backmatter; Back Cover.
This revised second edition presents an introduction to statistical pattern recognition. Pattern recognition in general covers a range of problems: it is applied to engineering problems, such as character readers and wave form analysis as well as to brain modeling in biology and psychology.