Please use this identifier to cite or link to this item: https://doi.org/10.1109/SIPS.2007.4387614
Title: Adaptive noise subspace estimation algorithm with an optimal diagonal-matrix step-size
Authors: Yang, L.
Attallah, S. 
Keywords: Adaptive signal processing
Diagonal-matrix step-size
Noise subspace estimation
Optimal step-size
Issue Date: 2007
Source: Yang, L., Attallah, S. (2007). Adaptive noise subspace estimation algorithm with an optimal diagonal-matrix step-size. IEEE Workshop on Signal Processing Systems, SiPS: Design and Implementation : 584-588. ScholarBank@NUS Repository. https://doi.org/10.1109/SIPS.2007.4387614
Abstract: In this paper, we propose a new optimal diagonal-matrix stepsize for the fast data projection method (FDPM) algorithm. The proposed step-sizes control the decoupled subspace vectors individually as compared to conventional methods where all the subspace vectors are multiplied by the same step-size value (scalar case). Simulation results show that FDPM with this optimal diagonal-matrix step-size outperforms the original algorithm as it offers faster convergence rate, smaller steady state error and smaller orthogonality error simultaneously. The proposed method can easily be applied to other subspace algorithms as well. © 2007 IEEE.
Source Title: IEEE Workshop on Signal Processing Systems, SiPS: Design and Implementation
URI: http://scholarbank.nus.edu.sg/handle/10635/69211
ISBN: 1424412226
ISSN: 15206130
DOI: 10.1109/SIPS.2007.4387614
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

20
checked on Dec 10, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.