A method for speeding up feature extraction based on KPCA

Neurocomputing

Volumn 70, Issue 4-6, 2007, Pages 1056-1061

  Xu, Yong ^a   Zhang, David ^b   Song, Fengxi ^a   Yang, Jing Yu ^c   Jing, Zhong ^c   Li, Miao ^a  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

^b HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^c NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Feature extraction; Improved KPCA (IKPCA); Kernel PCA (KPCA); Principal component analysis (PCA)

Indexed keywords

DATA PROCESSING; NUMERICAL METHODS; PRINCIPAL COMPONENT ANALYSIS;

DATASETS; FEATURE EXTRACTION PROCESS; KERNEL PRINCIPAL COMPONENT ANALYSIS (KPCA);

FEATURE EXTRACTION;

ACCURACY; ANALYTICAL ERROR; ARTICLE; CLASSIFICATION; CONTROLLED STUDY; DISCRIMINANT ANALYSIS; INTERMETHOD COMPARISON; KERNEL METHOD; MATHEMATICAL COMPUTING; METHODOLOGY; PATTERN RECOGNITION; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; QUALITY CONTROL; STATISTICAL ANALYSIS;

EID: 33845973353     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2006.09.005     Document Type: Article

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