Sparse coding and rough set theory-based hybrid approach to the classificatory decomposition of cortical evoked potentials

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

Volumn 5, Issue , 2002, Pages 2264-2268

  Boratyn, G M ^a   Smolinski, T G ^a   Milanova, M ^b   Wrobel, A ^c  

^a University of Louisville   (United States)

^b University of Arkansas at Little Rock ^*  (United States)

^c NENCKI INSTITUTE OF EXPERIMENTAL BIOLOGY   (Poland)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; CODES (SYMBOLS); COMPUTATION THEORY; ELECTROPHYSIOLOGY; FUNCTIONS; HYBRID SYSTEMS; INDEPENDENT COMPONENT ANALYSIS; INFORMATION SCIENCE; NEURAL NETWORKS; PRINCIPAL COMPONENT ANALYSIS; SET THEORY; SIGNAL DISTORTION; SIGNAL PROCESSING;

HYBRID APPROACH; OVER-COMPLETE REPRESENTATIONS; PRINCIPLE COMPONENT ANALYSIS; PROBABILISTIC MODELING; SELECTION MECHANISM; SIGNAL CLASSIFICATION; SIGNAL DECOMPOSITION; SIGNAL DECOMPOSITION TECHNIQUE;

ROUGH SET THEORY;

EID: 84971607422     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICONIP.2002.1201896     Document Type: Conference Paper

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