Hidden Markov Model Decorrelated Diffusion Leaky LMS With Optimized Leaky Factor

In this paper, two basic novel modifications of Diffusion Leaky Least Mean Square (DL-LMS) algorithm are proposed. First, the optimized leaky factor is obtained in closed form using the minimum disturbance principle, thanks to quadratic form of disturbance. Then, a low complexity decorrelated versio...

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Main Authors: Hadi Zayyani, Mohammad Salman, Mehdi Korki, Ahmed A. F. Youssef
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10464311/
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author Hadi Zayyani
Mohammad Salman
Mehdi Korki
Ahmed A. F. Youssef
author_facet Hadi Zayyani
Mohammad Salman
Mehdi Korki
Ahmed A. F. Youssef
author_sort Hadi Zayyani
collection DOAJ
description In this paper, two basic novel modifications of Diffusion Leaky Least Mean Square (DL-LMS) algorithm are proposed. First, the optimized leaky factor is obtained in closed form using the minimum disturbance principle, thanks to quadratic form of disturbance. Then, a low complexity decorrelated version of DL-LMS is presented based on the statistical Hidden Markov Modeling (HMM) of time correlations of input signals. The decorrelation is performed using a simple one-tap filter. Simulation results demonstrate the effectiveness of both modifications in comparison to other methods.
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spelling doaj.art-7ee5dcfb8296420eb57f4a3c3983dcce2024-04-04T23:00:26ZengIEEEIEEE Access2169-35362024-01-0112398043981010.1109/ACCESS.2024.337575710464311Hidden Markov Model Decorrelated Diffusion Leaky LMS With Optimized Leaky FactorHadi Zayyani0https://orcid.org/0000-0001-6350-6541Mohammad Salman1https://orcid.org/0000-0002-1769-6652Mehdi Korki2https://orcid.org/0000-0002-9914-1852Ahmed A. F. Youssef3Department of Electrical and Computer Engineering, Qom University of Technology (QUT), Qom, IranCollege of Engineering and Technology, American University of the Middle East, Egaila, KuwaitSchool of Science, Computing, and Engineering Technologies, Swinburne University of Technology, Melbourne, VIC, AustraliaCollege of Engineering and Technology, American University of the Middle East, Egaila, KuwaitIn this paper, two basic novel modifications of Diffusion Leaky Least Mean Square (DL-LMS) algorithm are proposed. First, the optimized leaky factor is obtained in closed form using the minimum disturbance principle, thanks to quadratic form of disturbance. Then, a low complexity decorrelated version of DL-LMS is presented based on the statistical Hidden Markov Modeling (HMM) of time correlations of input signals. The decorrelation is performed using a simple one-tap filter. Simulation results demonstrate the effectiveness of both modifications in comparison to other methods.https://ieeexplore.ieee.org/document/10464311/Distributed estimationleaky LMShidden Markov modeldiffusion
spellingShingle Hadi Zayyani
Mohammad Salman
Mehdi Korki
Ahmed A. F. Youssef
Hidden Markov Model Decorrelated Diffusion Leaky LMS With Optimized Leaky Factor
IEEE Access
Distributed estimation
leaky LMS
hidden Markov model
diffusion
title Hidden Markov Model Decorrelated Diffusion Leaky LMS With Optimized Leaky Factor
title_full Hidden Markov Model Decorrelated Diffusion Leaky LMS With Optimized Leaky Factor
title_fullStr Hidden Markov Model Decorrelated Diffusion Leaky LMS With Optimized Leaky Factor
title_full_unstemmed Hidden Markov Model Decorrelated Diffusion Leaky LMS With Optimized Leaky Factor
title_short Hidden Markov Model Decorrelated Diffusion Leaky LMS With Optimized Leaky Factor
title_sort hidden markov model decorrelated diffusion leaky lms with optimized leaky factor
topic Distributed estimation
leaky LMS
hidden Markov model
diffusion
url https://ieeexplore.ieee.org/document/10464311/
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AT mohammadsalman hiddenmarkovmodeldecorrelateddiffusionleakylmswithoptimizedleakyfactor
AT mehdikorki hiddenmarkovmodeldecorrelateddiffusionleakylmswithoptimizedleakyfactor
AT ahmedafyoussef hiddenmarkovmodeldecorrelateddiffusionleakylmswithoptimizedleakyfactor