An Efficient Adaptive Minor Subspace Extraction Using Exact Nested Orthogonal Complement Structure

• MISONO Masaki

  Dept. of Communications & Integrated Systems, Tokyo Institute of Technology

• YAMADA Isao

  Dept. of Communications & Integrated Systems, Tokyo Institute of Technology The Institute of Electronics, Information and Communication Engineers

抄録

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.

収録刊行物

• IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

  IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E91-A (8), 1867-1874, 2008

  一般社団法人 電子情報通信学会

キーワード

• adaptive minor subspace extraction
• nested orthogonal complement subspaces
• modified Oja-Xu MCA learning

詳細情報

• CRID: 1390282681288253312
• NII論文ID: 10026850400
• NII書誌ID: AA10826239
• DOI: 10.1093/ietfec/e91-a.8.1867
• ISSN: 17451337
• ISSN: 09168508
• Web Site: https://www.jstage.jst.go.jp/article/transfun/E91.A/8/E91.A_8_1867/_pdf
• 本文言語コード: en
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