Robust Incremental Least Mean Square Algorithm With Dynamic Combiner Article Swipe
Syed Safi Uddin Qadri
,
Muhammad Arif
,
Imran Naseem
,
Muhammad Moinuddin
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1109/access.2022.3192018
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1109/access.2022.3192018
In distributed wireless networks, the adaptation process depends on the information being shared between various nodes. The global minimum, is therefore, likely to be affected when the information shared between the nodes gets corrupted. This could happen due to several reasons namely link failure, noisy environment and erroneous data etc. In this research, we propose a computationally efficient robust incremental least mean square (RILMS) algorithm to resolve the aforementioned issues. Essentially, a fusion step is introduced in the framework of the incremental least mean square (ILMS). Prior to adaptation at a node, the information shared by the neighbouring node is fused with the temporally preceding information of the node using an efficient combiner. An adaptive fusion strategy is proposed resulting in dynamic weight assignment for the fusion step. Closed form expression for the steady-state excess mean square error (EMSE) is derived and the performance of the proposed algorithm is evaluated for the noisy link environments and compared to the existing algorithms. Extensive experiments show the efficacy of the proposed approach compared to the contemporary methods. The proposed algorithm is found to be robust against the link failure and local node divergence problems. The improved performance of the proposed RILMS algorithm comes with a significant reduction in computational complexity compared to the convex combination based ILMS (CILMS) approach.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/access.2022.3192018
- https://ieeexplore.ieee.org/ielx7/6287639/6514899/09832595.pdf
- OA Status
- gold
- Cited By
- 6
- References
- 37
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4285820243
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4285820243Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/access.2022.3192018Digital Object Identifier
- Title
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Robust Incremental Least Mean Square Algorithm With Dynamic CombinerWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-01-01Full publication date if available
- Authors
-
Syed Safi Uddin Qadri, Muhammad Arif, Imran Naseem, Muhammad MoinuddinList of authors in order
- Landing page
-
https://doi.org/10.1109/access.2022.3192018Publisher landing page
- PDF URL
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https://ieeexplore.ieee.org/ielx7/6287639/6514899/09832595.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://ieeexplore.ieee.org/ielx7/6287639/6514899/09832595.pdfDirect OA link when available
- Concepts
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Computer science, Node (physics), Algorithm, Mean squared error, Divergence (linguistics), Computational complexity theory, Minimum mean square error, Reduction (mathematics), Mathematics, Statistics, Engineering, Philosophy, Structural engineering, Estimator, Linguistics, GeometryTop concepts (fields/topics) attached by OpenAlex
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6Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2024: 1, 2023: 3Per-year citation counts (last 5 years)
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37Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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