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@article{Xiang:2016:10.1016/j.sigpro.2016.10.007,
author = {Xiang, M and Took, CC and Mandic, DP},
doi = {10.1016/j.sigpro.2016.10.007},
journal = {Signal Processing},
pages = {81--91},
title = {Cost-effective quaternion minimum mean square error estimation: From widely linear to four-channel processing},
url = {http://dx.doi.org/10.1016/j.sigpro.2016.10.007},
volume = {136},
year = {2016}
}
TY - JOUR
AB - Widely linear estimation plays an important role in quaternion signal processing, as it caters for both proper and improper quaternion signals. However, widely linear algorithms are computationally expensive owing to the use of augmented variables and statistics. To reduce the computation cost while maintaining the performance level, we propose a four-channel estimation framework as an efficient alternative to quaternion widely linear estimation. This is achieved by using four linear models to estimate the four components of quaternion signals. We also show that any of the four channels is able to replace a strictly linear quaternion estimator when estimating strictly linear systems. The proposed method is shown to reduce computational complexity and provide more flexible algorithms, while preserving the physical meaning inherent in the quaternion domain. The proposed framework is next applied to quaternion minimum mean square error estimation to yield the reduced-complexity versions of the quaternion least mean square (QLMS), quaternion recursive least squares (QRLS), and quaternion nonlinear gradient decent (QNGD) algorithms. For the proposed QLMS algorithm, an adaptive step-size strategy is also explored. The effectiveness of the so introduced estimation techniques is validated by simulations on synthetic and real-world signals.
AU - Xiang,M
AU - Took,CC
AU - Mandic,DP
DO - 10.1016/j.sigpro.2016.10.007
EP - 91
PY - 2016///
SN - 0165-1684
SP - 81
TI - Cost-effective quaternion minimum mean square error estimation: From widely linear to four-channel processing
T2 - Signal Processing
UR - http://dx.doi.org/10.1016/j.sigpro.2016.10.007
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000398878200009&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR - http://hdl.handle.net/10044/1/49972
VL - 136
ER -
