The nonlinear PCA criterion in blind source separation: Relations with other approaches

Neurocomputing

Volumn 22, Issue 1-3, 1998, Pages 5-20

  Karhunen, Juha ^a   Pajunen, Petteri ^a   Oja, Erkki ^a  

^a AALTO UNIVERSITY   (Finland)

Author keywords

Blind separation; Least squares; Neural networks; Nonlinear PCA; Unsupervised learning

Indexed keywords

ADAPTIVE ALGORITHMS; COMPUTATIONAL COMPLEXITY; CONVERGENCE OF NUMERICAL METHODS; FUNCTIONS; LEAST SQUARES APPROXIMATIONS; SIGNAL THEORY; STATISTICAL METHODS;

BELL-SEJNOWSKI ALGORITHMS; BLIND SOURCE SEPARATIONS; NONLINEAR PRINCIPAL COMPONENT ANALYSIS;

NEURAL NETWORKS;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; MATHEMATICAL ANALYSIS; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; REVIEW; STATISTICAL ANALYSIS;

EID: 0032212834     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0925-2312(98)00046-0     Document Type: Article

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