A principal component analysis algorithm with invariant norm

Neurocomputing

Volumn 8, Issue 2, 1995, Pages 213-221

  Luo, Fa Long ^a,b   Unbehauen, Rolf ^a   Li, Yan Da ^b  

^a UNIVERSITY OF ERLANGEN NUREMBERG   (Germany)

^b TSINGHUA UNIVERSITY   (China)

Author keywords

Adaptive signal processing; Eigenvectors; Neural networks; Unsupervised learning

Indexed keywords

ALGORITHM; ARTICLE; COMPUTER ANALYSIS; COMPUTER MODEL; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; PRIORITY JOURNAL; SIGNAL PROCESSING;

EID: 0029004784     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/0925-2312(95)00044-7     Document Type: Article

References (6)

1. Representation and separation of signals using nonlinear PCA type learning
2. Optimal unsupervised learning in a single-layer linear feedforward neural network
3. Analysis of recursive stochastic algorithm
4. Modified Hebbian learning for curve and surface fitting