DocumentCode
1239175
Title
A new minor component analysis method based on Douglas-Kung-Amari minor subspace analysis method
Author
Jankovic, Marko V. ; Reljin, Branimir
Author_Institution
Inst. of Electr. Eng., Belgrade, Serbia
Volume
12
Issue
12
fYear
2005
Firstpage
859
Lastpage
862
Abstract
This letter presents a new minor component analysis algorithm that is based on the transformation of the known minor subspace analysis algorithm. The minor subspace analysis method that is adopted is the one proposed by Douglas, Kung, and Amari. The proposed minor component analysis algorithm extracts N minor components of the K-dimensional vector stationary random process N\n\n\t\t
Keywords
adaptive signal processing; neural nets; principal component analysis; random processes; Douglas-Kung-Amari MSA; K-dimensional vector; MCA algorithm; adaptive algorithm; individual neuron; minor component analysis; minor subspace analysis method; stationary random process; Algorithm design and analysis; Covariance matrix; Data mining; Differential equations; Hardware; Learning systems; Neurons; Random processes; Signal processing algorithms; Stochastic processes; Adaptive algorithm; minor component analysis (MCA);
fLanguage
English
Journal_Title
Signal Processing Letters, IEEE
Publisher
ieee
ISSN
1070-9908
Type
jour
DOI
10.1109/LSP.2005.859497
Filename
1542118
Link To Document