A novel neural-network approach of analog fault diagnosis based on kernel discriminant analysis and particle swarm optimization

Applied Soft Computing Journal

Volumn 12, Issue 2, 2012, Pages 904-920

  Xiao, Yingqun ^a   Feng, Lianggui ^a  

^a NATIONAL UNIVERSITY OF DEFENSE TECHNOLOGY   (China)

Author keywords

Analog circuits; Fault diagnosis; Kernel linear discriminant analysis (KLDA); Kernel principal component analysis (KPCA); Maximal class separability; Neural network; Particle swarm optimization

Indexed keywords

ANALOG FAULT; ANALOG FAULT DIAGNOSIS; CLASS SEPARABILITY; DIMENSIONALITY REDUCTION; KERNEL DISCRIMINANT ANALYSIS; KERNEL PRINCIPAL COMPONENT ANALYSIS; LINEAR DISCRIMINANT ANALYSIS; PARTICLE SWARM;

ANALOG CIRCUITS; BACKPROPAGATION ALGORITHMS; DISCRIMINANT ANALYSIS; FACE RECOGNITION; FAILURE ANALYSIS; FEATURE EXTRACTION; NETWORKS (CIRCUITS); NEURAL NETWORKS; PARTICLE SWARM OPTIMIZATION (PSO);

PRINCIPAL COMPONENT ANALYSIS;

EID: 84655169868     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2011.10.002     Document Type: Article

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