Diffusion inverse Square-root Recursive Least Square-based Algorithm with Adaptive Network

dc.contributor.authorSuchada Sitjongsataporn
dc.contributor.authorSethakarn Prongnuch
dc.contributor.authorTheerayod Wiangtong
dc.date.accessioned2026-05-08T19:20:03Z
dc.date.issued2021-5-19
dc.description.abstractIn this paper, a Combine-Then-Adapt diffusion strategy on adaptive recursive least square algorithm (RLS) is proposed with adaptive network. We apply the inverse autocorrelation matrix based on the QR-decomposition method in order to reduce the complexity. The Combine-Then-Adapt diffusion strategy is modified on the inverse square-root recursive least square (iQR-RLS) algorithm including with the combination and adaptation steps. By applying an idea of diffusion strategy and mixed cost function, we derive a diffused version of an inverse square-root recursive least square algorithm, named as DiQR-RLS. Experimental results demonstrate that the proposed DiQR-RLS can achieve clearly the better performance than the conventional recursive least square algorithm.
dc.identifier.doi10.1109/ecti-con51831.2021.9454860
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/17311
dc.subjectAdvanced Adaptive Filtering Techniques
dc.subjectImage and Signal Denoising Methods
dc.subjectNeural Networks and Applications
dc.titleDiffusion inverse Square-root Recursive Least Square-based Algorithm with Adaptive Network
dc.typeArticle

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