Accession Number:

AD0758472

Title:

Statistical Pattern Recognition,

Descriptive Note:

Corporate Author:

SOUTHEASTERN MASSACHUSETTS UNIV NORTH DARTMOUTH DEPT OF ELECTRICAL ENGINEERING

Personal Author(s):

Report Date:

1973-01-01

Pagination or Media Count:

247.0

Abstract:

The text presents a concise, up-to-date treatment of the fundamental concepts and techniques in statistical pattern recognition. It offers broad and balanced views on various approaches that have widespread application not only in designing better recognition machines, but also in such areas as statistical data processing, communication and control systems, and the computer-related fields. Discussions of linear and non-linear classification theories, representation of patterns, and feature selection using information statistics provide a basic understanding of the subject. Parametric and nonparametric methods of recognition with unknown or partially unknown probability density functions are covered in great detail. An alternative approach to pattern recognition is discussed in a chapter devoted to sequential decision making, feature ordering, and the application of learning algorithms to communication theory and systems. Author

Subject Categories:

  • Statistics and Probability
  • Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE