Title :
The widely linear quaternion recursive total least squares
Author :
Thanthawaritthisai, Thiannithi ; Tobar, Felipe ; Constantinides, Anthony G. ; Mandic, Danilo P.
Author_Institution :
Dept. of Electr. & Electron. Eng., Imperial Coll. London, London, UK
Abstract :
A widely linear quaternion recursive total least squares (WL-QRTLS) algorithm is introduced for the processing of ℚ-improper processes contaminated by noise. The total least squares for quaternions (QTLS) is a generalisation of the real-valued total least squares and is introduced rigorously, starting from the existence condition for low-rank approximation of quaternion matrices. Then, a quaternion Rayleigh quotient (QRQ) is defined to establish the link between the QTLS solution and the minimisation of the QRQ. Finally, the rank-one update formula is employed to allow for fast iterative solution based on the QRQ. Through simulations, the WL-QRTLS was shown to exhibit superior performance, under perturbations on both input and output signals, to other adaptive filtering of the same class - the widely linear quaternion least mean squares (WL-QLMS) and the widely linear quaternion recursive least squares (WL-QRLS). The experiments on both synthetic and real-world ℚ-improper processes supported the analysis.
Keywords :
adaptive filters; iterative methods; least mean squares methods; ℚ-improper process; QRQ; WL-QRTLS algorithm; adaptive filtering; fast iterative solution; low-rank approximation; quaternion Rayleigh quotient; widely linear quaternion recursive total least squares algorithm; Indexes; Least squares approximations; Matrices; Noise; Quaternions; Signal processing algorithms; Rayleigh quotient; low-rank approximation; quaternions; total least squares; widely linear QRTLS;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on
Conference_Location :
South Brisbane, QLD
DOI :
10.1109/ICASSP.2015.7178593