The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
이 논문은 공분산 행렬의 단일 소고유벡터를 근사화하기 위한 Peng과 Yi('07)의 아이디어를 기반으로 하는 새로운 적응형 소부분공간 추출 알고리즘을 제시합니다. 제안된 알고리즘은 중첩된 직교 보완 부분 공간에서 아이디어를 귀납적으로 활용함으로써 Oja 알고리즘('82) 및 안정화된 버전인 O-Oja 알고리즘( '02). 시뮬레이션 결과는 제안한 알고리즘이 O-Oja 알고리즘보다 더 안정적인 수렴을 구현함을 보여준다.
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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},}
부
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 -