The chain-rule processor: Optimal classification through signal processing

Proceedings - International Conference on Pattern Recognition

Volumn 16, Issue 1, 2002, Pages 230-234

  Baggenstoss, Paul M ^a  

^a NAVAL UNDERSEA WARFARE CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); DATA REDUCTION; FEATURE EXTRACTION; THEOREM PROVING; CHAINS; PATTERN RECOGNITION;

BAYES CLASSIFIERS; CHAIN-RULE PROCESSORS; CLASS-SPECIFIC FEATURES;

SIGNAL PROCESSING;

CHAIN RULES; CLASS SPECIFIC FEATURES; CURSE OF DIMENSIONALITY; FEATURE EXTRACTOR; OPTIMAL BAYES CLASSIFIER; OPTIMAL CLASSIFICATION; OPTIMAL CLASSIFIERS; PROJECTION THEOREM;

EID: 33751575050     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Article

References (6)

1. P. M. Baggenstoss, "A theoretically optimum approach to classification using class-specific features.," Proceedings of ICPR, Barcelona, 2000.
2. P. M. Baggenstoss, "A modified Baum-Weich algorithm for hidden Markov models with multiple observation spaces.," IEEE Trans. Speech and Audio, pp. 411-416, May 2001.
3. S. M. Kay, A. H. Nuttall, and P. M. Baggenstoss, "Multidimensional probability density function approximation for detection, classification and model order selection," IEEE Trans. Signal Processing, Oct 2001.
4. P. M. Baggenstoss, "Structural learning for classification of high dimensional data," in Proceedings of the 1997 International Conference on Intelligent Systems and Semiotics, pp. 124-129, National Institute of Standards and Technology, 1997.
5. S. Kay, Modern Spectral Estimation: Theory and Applications. Prentice Hall, 1988.
6. P. Baggenstoss, "Class-specific web page," http://www.npt.nuwc. navy.mil/csf/index.htinl.