Multichannel Quaternion Least Mean Square Algorithm

Clive Cheong Took; Yili Xia

doi:10.1109/ICASSP.2019.8682795

Multichannel Quaternion Least Mean Square Algorithm

Clive Cheong Took, Yili Xia

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Abstract

Quaternion least-mean-quare (QLMS) algorithm has been thoroughly investigated in the past for the adaptive filtering of 3D and 4D signals. However, QLMS is restricted to one-channel processing of such 3D and 4D processes. To address this shortcoming, we proposed the multichannel QLMS so that we can exploit the additional information from the multitude of 3D-4D vector sensors. For rigour, we provide the stability bound of the multichannel QLMS and demonstrate its robustness against noise. Simulations on real world 4D signals support the analysis.

Original language	English
Title of host publication	International Conference on Acoustics, Speech, and Signal Processing
Subtitle of host publication	ICASSP
Place of Publication	Brighton UK
Publisher	IEEE
Pages	1-4
Number of pages	4
ISBN (Electronic)	978-1-4799-8131-1
DOIs	https://doi.org/10.1109/ICASSP.2019.8682795
Publication status	E-pub ahead of print - 17 Apr 2019

Keywords

Signal Processing
adaptive filters
quaternion
machine learning

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10.1109/ICASSP.2019.8682795

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title = "Multichannel Quaternion Least Mean Square Algorithm",

abstract = "Quaternion least-mean-quare (QLMS) algorithm has been thoroughly investigated in the past for the adaptive filtering of 3D and 4D signals. However, QLMS is restricted to one-channel processing of such 3D and 4D processes. To address this shortcoming, we proposed the multichannel QLMS so that we can exploit the additional information from the multitude of 3D-4D vector sensors. For rigour, we provide the stability bound of the multichannel QLMS and demonstrate its robustness against noise. Simulations on real world 4D signals support the analysis.",

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AU - Xia, Yili

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N2 - Quaternion least-mean-quare (QLMS) algorithm has been thoroughly investigated in the past for the adaptive filtering of 3D and 4D signals. However, QLMS is restricted to one-channel processing of such 3D and 4D processes. To address this shortcoming, we proposed the multichannel QLMS so that we can exploit the additional information from the multitude of 3D-4D vector sensors. For rigour, we provide the stability bound of the multichannel QLMS and demonstrate its robustness against noise. Simulations on real world 4D signals support the analysis.

AB - Quaternion least-mean-quare (QLMS) algorithm has been thoroughly investigated in the past for the adaptive filtering of 3D and 4D signals. However, QLMS is restricted to one-channel processing of such 3D and 4D processes. To address this shortcoming, we proposed the multichannel QLMS so that we can exploit the additional information from the multitude of 3D-4D vector sensors. For rigour, we provide the stability bound of the multichannel QLMS and demonstrate its robustness against noise. Simulations on real world 4D signals support the analysis.

KW - Signal Processing

KW - adaptive filters

KW - quaternion

KW - machine learning

UR - https://2019.ieeeicassp.org/

U2 - 10.1109/ICASSP.2019.8682795

DO - 10.1109/ICASSP.2019.8682795

M3 - Conference contribution

SP - 1

EP - 4

BT - International Conference on Acoustics, Speech, and Signal Processing

PB - IEEE

CY - Brighton UK

ER -

Multichannel Quaternion Least Mean Square Algorithm

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Keywords

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