A deterministic analysis of linearly constrained adaptive filtering algorithms

Masahiro Yukawa, Isao Yamada

研究成果: Conference article査読

3 被引用数 (Scopus)

抄録

This paper presents a mathematically rigorous analysis of linearly constrained adaptive filtering algorithms based on the adaptive projected subgradient method. We provide the novel concept of constraint-embedding functions that enables to analyze certain classes of linearly constrained adaptive algorithms in a unified manner. Trajectories of the linearly constrained adaptive filters always lie in the affine constraint set, a translation of a closed subspace. Based on this fact, we translate all the points on the constraint set to its underlying subspace . which we regard as a Hilbert space . thereby making the analysis feasible. Derivations of the linearly constrained adaptive filtering algorithms are finally presented in connection with the analysis.

本文言語English
ページ(範囲)131-135
ページ数5
ジャーナルEuropean Signal Processing Conference
出版ステータスPublished - 2011 12月 1
外部発表はい
イベント19th European Signal Processing Conference, EUSIPCO 2011 - Barcelona, Spain
継続期間: 2011 8月 292011 9月 2

ASJC Scopus subject areas

  • 信号処理
  • 電子工学および電気工学

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