Feature extraction using supervised independent component analysis by maximizing class distance

ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age

Volumn 5, Issue , 2002, Pages 2502-2506

  Sakaguchi, Y ^a   Ozawa, S ^a   Kotani, M ^a  

^a KOBE UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BLIND SOURCE SEPARATION; EXTRACTION; FEATURE EXTRACTION; INFORMATION SCIENCE; LEARNING SYSTEMS;

BLIND SIGNAL SEPARATION; CLASS SEPARABILITY; INDEPENDENT COMPONENT ANALYSIS(ICA); MAHALANOBIS DISTANCES; PERFORMANCE PATTERNS; PRINCIPAL COMPONENTS; RECOGNITION ACCURACY; UCI MACHINE LEARNING REPOSITORY;

INDEPENDENT COMPONENT ANALYSIS;

EID: 84971645584     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICONIP.2002.1201945     Document Type: Conference Paper

References (10)

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10. http://www.ics.uci.edu/mlearn/MLRepository.html