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Paper data
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Title:
Multi-Stage Reduced-Rank Adaptive Filter With Flexible Structure

Author(s):
Burykh Serguei, ENST PARIS, Signal and Image Processing dept.
Abed Meraim Karim, ENST PARIS, Signal and Image Processing dept.

Page numbers in the proceedings:
Volume III pp 221-224

Session:
Beamforming and Spatial Filtering

Paper abstract
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An adaptive reduced-rank filter based on Conjugate-Gradient Algorithm is presented - Conjugate-Gradient Reduced-Rank Filter (CGRRF). The proposed method computes reduced-rank Wiener solutions iteratively starting from rank 1 (matched filter). It is shown that any of these filters is equivalent to the Multi-Stage Wiener Filter proposed by Goldstein and Reed of a particular rank. Contrary to other techniques of comparable performance, the rank of CGRRF (number of stages) can be easily adapted to achieve required performance/complexity trade-off. This property is illustrated numerically using adaptive rank selection technique along with other examples showing good transient and asymptotic performance of the method.

Paper
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A PDF version is available here

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