Reduced-rank adaptive filtering using Krylov subspace

Authors:
Sergueï Burykh;Karim Abed-Meraim
Affiliations:
Signal and Image Processing Department of École Nationale Supérieure des Télécommunications, Paris, France;Signal and Image Processing Department of École Nationale Supérieure des Télécommunications, Paris, France
Venue:
EURASIP Journal on Applied Signal Processing
Year:
2002

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Abstract

A unified view of several recently introduced reduced-rank adaptive filters is presented. As all considered methods use Krylov subspace for rank reduction, the approach taken in this work is inspired from Krylov subspace methods for iterative solutions of linear systems. The alternative interpretation so obtained is used to study the properties of each considered technique and to relate one reduced-rank method to another as well as to algorithms used in computational linear algebra. Practical issues are discussed and low-complexity versions are also included in our study. It is believed that the insight developed in this paper can be further used to improve existing reduced-rank methods according to known results in the domain of Krylov subspace methods.