A parametric classification rule based on the exponentially embedded family

IEEE Transactions on Neural Networks and Learning Systems

Volumn 26, Issue 2, 2015, Pages 367-377

  Tang, Bo ^a   He, Haibo ^a   Ding, Quan ^b   Kay, Steven ^a  

^a The University of Rhode Island   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Exponentially embedded family (EEF); multivariate Gaussian classification; parametric classification rule.

Indexed keywords

MONTE CARLO METHODS; PATTERN RECOGNITION; PROBABILITY DENSITY FUNCTION;

CLASSIFICATION PERFORMANCE; EXPONENTIALLY EMBEDDED FAMILIES; GAUSSIAN CLASSIFICATIONS; MODEL ORDER ESTIMATION; MULTIVARIATE PATTERNS; PARAMETRIC CLASSIFICATION; PARAMETRIC CLASSIFIER; POWER QUALITY DISTURBANCES;

CLASSIFICATION (OF INFORMATION);

EID: 85027953845     PISSN: 2162237X     EISSN: 21622388     Source Type: Journal    
DOI: 10.1109/TNNLS.2014.2383692     Document Type: Article

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