Robust Heteroscedastic Probabilistic Neural Network for multiple source partial discharge pattern recognition - Significance of outliers on classification capability

Expert Systems with Applications

Volumn 38, Issue 9, 2011, Pages 11501-11514

  Venkatesh, S ^a   Gopal, S ^b  

^a SASTRA UNIVERSITY   (India)

^b WS Test Systems Limited   (India)

Author keywords

Heteroscedastic Probabilistic Neural Network (HRPNN); Neural network (NN); Partial discharge (PD); Probabilistic Neural Network (PNN); Robust Heteroscedastic Neural Network (RHRPNN)

Indexed keywords

APPLIED VOLTAGES; DATA SETS; DISCHARGE PATTERNS; HANDLING POWER; HETEROSCEDASTIC; INSULATION DIAGNOSTICS; INSULATION SYSTEM; MULTIPLE SOURCE; MULTISOURCES; NON-INTRUSIVE; PARTIAL DISCHARGE PATTERN RECOGNITION; PD PATTERN; POWER APPARATUS; PRE-PROCESSING; PROBABILISTIC NEURAL NETWORKS; RESEARCH STUDIES; SINGLE SOURCE; SMOOTHING PARAMETER; SPLIT WINDOWS; STATISTICAL OPERATORS; TESTING STRATEGIES; WAVELET TRANSFORMATIONS; WEIBULL FUNCTIONS;

ENGINEERING RESEARCH; PARTIAL DISCHARGES; PATTERN RECOGNITION; PERSONNEL TESTING; PROBABILITY DENSITY FUNCTION; WEIBULL DISTRIBUTION;

NEURAL NETWORKS;

EID: 79955573457     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2011.03.026     Document Type: Article

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