A unified algorithm for principal and minor components extraction

 CHEN Tianping
 Department of Mathematics, Fudan University

 AMARI Shunichi
 RIKEN Brain Science Institute

 LIN Qin
 Department of Mathematics, Fudan University
Search this Article
Author(s)

 CHEN Tianping
 Department of Mathematics, Fudan University

 AMARI Shunichi
 RIKEN Brain Science Institute

 LIN Qin
 Department of Mathematics, Fudan University
Journal

 Neural Networks

Neural Networks 11(3), 385390, 19980401
References: 19

1
 Neural theory of association and conceptformation

AMARI S.
Biology Cybernetics 26, 175185, 1977
Cited by (2)

2
 <no title>

AMARI S.
DifferentialGeometrical Methods of Statistics. Springer Lecture Notes in Statistics, 28, 1985
Cited by (1)

3
 Information geometry

AMARI S.
Geometry and Nature. Contemporary Mathematics 203, 8195, 1997
Cited by (1)

4
 Modified Oja's algorithms for principal subspace and minor subspace extraction

CHEN T. P.
Neural Processing Letters 5, 105110, 1997
Cited by (2)

5
 <no title>

HELMKE U.
Optimization and Dynamical Systems, 1993
Cited by (1)

6
 Completely integrable gradient systems on the manifold of Gaussian and multinomial distributions

NAKAMURA Y.
Japan Journal of Applied and Industrial Mathematics 10, 179189, 1993
Cited by (1)

7
 A Simplified Neuron Model as a Principal Component Analyzer

OJA E.
J. Math. Biology 15, 267273, 1982
Cited by (4)

8
 Optimal unsupervised learning in a singlelayer linear feedforward network

SANGER T. D.
Neural Networks 2, 459573, 1989
Cited by (2)

9
 Natural gradient works efficiently in learning

AMARI S.
Neural Computation 10, 251276, 1998
DOI Cited by (145)

10
 Stability analysis of learning algorithms for blind source separation

AMARI S.
Neural Networks 10(8), 13451351, 1997
DOI Cited by (16)

11
 Least square matching problems

R. W. Brockett
Linear Algebra Appl. 122124, 761777, 1989
DOI Cited by (7)

12
 Dynamical systems that sort lists, diagonalize matrices and solve linear programming problems

BROCKETT R. W.
Lin. Algebra Appl. 146, 76/91, 1991
DOI Cited by (7)

13
 Global convergence of Oja's subspace algorithm for principal component extraction

CHEN T. P.
IEEE Transactions on Neural Networks 9, 5867, 1998
Cited by (3)

14
 Gradient systems in view of information geometry

A. Fujiwara
Physica D 80, 317327, 1995
Cited by (8)

15
 On stochastic approximation of the eigenvectors and eigenvalues of the expectation of a random matrix

OJA E.
Journal of Mathematical Analysis and Applications 106, 6984, 1985
DOI Cited by (13)

16
 Principal components, minor components and liner neural networks

OJA E.
Neural Netw. 5, 927935, 1992
Cited by (29)

17
 Modified Hebbian learning for curve and surface fitting

XU L.
Neural Networks 5(3), 441457, 1992
Cited by (14)

18
 Least Mean Square Error Reconstruction Principle for SelfOrganizing Neural Nets

XU L.
Neural Networks 6(5), 627648, 1993
Cited by (11)

19
 A unified neural bigradient algorithm for robust PCA and MCA

WANG L.
International J. Neural Systems 7(1), 5367, 1996
Cited by (3)
Cited by: 4

1
 A fast tracking algorithm for generalized eigenvectors of Hermitian matrices

TANAKA Toshihisa
IEICE technical report 108(390), 177182, 20090115
References (16)

2
 A fast tracking algorithm for generalized eigenvectors of Hermitian matrices

TANAKA Toshihisa
IEICE technical report 108(391), 177182, 20090115
References (16)

3
 Unified stabilization approach to principal and minor components extraction algorithms

CHEN Tianping , AMARI Shunichi
Neural Networks 14(10), 13771387, 20011201
References (20) Cited by (3)

4
 NumericallyStabilizing Method for Extraction of Principal and Minor Components [in Japanese]

MATSUKUBO Jun , HAYASHI Yukio
The Transactions of the Institute of Electronics,Information and Communication Engineers. A 85(9), 954966, 20020901
References (11)