Simultaneous extraction of principal components using givens rotations and output variances

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn 1, Issue , 2002, Pages

  Erdogmus, Deniz ^a   Rao, Yadunandana N ^a   Principe, Jose C ^a   Zhao, Jing ^a   Hild II, Kenneth E ^a  

^a UNIVERSITY OF FLORIDA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CONSTRAINED LINEAR NETWORK; EIGENVECTOR MATRIX;

ALGORITHMS; CONVERGENCE OF NUMERICAL METHODS; EIGENVALUES AND EIGENFUNCTIONS; FEATURE EXTRACTION; MATRIX ALGEBRA; PRINCIPAL COMPONENT ANALYSIS; TOPOLOGY;

SIGNAL PROCESSING;

EID: 0036293707     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. Adaptive principal component extraction (APEX) and applications
2. Artificial neural networks for feature extraction and multivariate data projection
3. Multichannel speech separation by eigendecomposition and its application to co-talker interference removal
4. Optimal unsupevised learning in a single layer linear feedforward neural network
5. Development of feature detectors by self organization
6. A self organizing network for principal component analysis
7. A fast, on-line algorithm for PCA and its convergence characteristics
8. Least mean square error reconstruction principle for self-organizing neural-nets
9. Blind source separation using Renyi's mutual information