An Efficient Adaptive Minor Subspace Extraction Using Exact Nested Orthogonal Complement Structure
Summary :
This paper presents a new adaptive minor subspace extraction algorithm based on an idea of Peng and Yi ('07) for approximating the single minor eigenvector of a covariance matrix. By utilizing the idea inductively in the nested orthogonal complement subspaces, the proposed algorithm succeeds to relax the numerical sensitivity which has been annoying conventional adaptive minor subspace extraction algorithms for example, Oja algorithm ('82) and its stabilized version: O-Oja algorithm ('02). Simulation results demonstrate that the proposed algorithm realizes more stable convergence than O-Oja algorithm.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E91-A No.8 pp.1867-1874
- Publication Date
- 2008/08/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1093/ietfec/e91-a.8.1867
- Type of Manuscript
- Special Section PAPER (Special Section on Signal Processing)
- Category
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Masaki MISONO, Isao YAMADA, "An Efficient Adaptive Minor Subspace Extraction Using Exact Nested Orthogonal Complement Structure" in IEICE TRANSACTIONS on Fundamentals,
vol. E91-A, no. 8, pp. 1867-1874, August 2008, doi: 10.1093/ietfec/e91-a.8.1867.
Abstract: This paper presents a new adaptive minor subspace extraction algorithm based on an idea of Peng and Yi ('07) for approximating the single minor eigenvector of a covariance matrix. By utilizing the idea inductively in the nested orthogonal complement subspaces, the proposed algorithm succeeds to relax the numerical sensitivity which has been annoying conventional adaptive minor subspace extraction algorithms for example, Oja algorithm ('82) and its stabilized version: O-Oja algorithm ('02). Simulation results demonstrate that the proposed algorithm realizes more stable convergence than O-Oja algorithm.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e91-a.8.1867/_p
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@ARTICLE{e91-a_8_1867,
author={Masaki MISONO, Isao YAMADA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={An Efficient Adaptive Minor Subspace Extraction Using Exact Nested Orthogonal Complement Structure},
year={2008},
volume={E91-A},
number={8},
pages={1867-1874},
abstract={This paper presents a new adaptive minor subspace extraction algorithm based on an idea of Peng and Yi ('07) for approximating the single minor eigenvector of a covariance matrix. By utilizing the idea inductively in the nested orthogonal complement subspaces, the proposed algorithm succeeds to relax the numerical sensitivity which has been annoying conventional adaptive minor subspace extraction algorithms for example, Oja algorithm ('82) and its stabilized version: O-Oja algorithm ('02). Simulation results demonstrate that the proposed algorithm realizes more stable convergence than O-Oja algorithm.},
keywords={},
doi={10.1093/ietfec/e91-a.8.1867},
ISSN={1745-1337},
month={August},}
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TY - JOUR
TI - An Efficient Adaptive Minor Subspace Extraction Using Exact Nested Orthogonal Complement Structure
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1867
EP - 1874
AU - Masaki MISONO
AU - Isao YAMADA
PY - 2008
DO - 10.1093/ietfec/e91-a.8.1867
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E91-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2008
AB - This paper presents a new adaptive minor subspace extraction algorithm based on an idea of Peng and Yi ('07) for approximating the single minor eigenvector of a covariance matrix. By utilizing the idea inductively in the nested orthogonal complement subspaces, the proposed algorithm succeeds to relax the numerical sensitivity which has been annoying conventional adaptive minor subspace extraction algorithms for example, Oja algorithm ('82) and its stabilized version: O-Oja algorithm ('02). Simulation results demonstrate that the proposed algorithm realizes more stable convergence than O-Oja algorithm.
ER -
English
