Diffusion Mixed-Node Recursive Least Square-based Algorithm over Adaptive Network

dc.contributor.authorSuchada Sitjongsataporn
dc.contributor.authorSethakarn Prongnuch
dc.contributor.authorTheerayod Wiangtong
dc.date.accessioned2026-05-08T19:22:49Z
dc.date.issued2022-3-9
dc.description.abstractThis paper proposes a diffusion framework related on the mixed-node constraint based on recursive least squares (RLS) algorithm with adaptive network. The proposed Combine-Then-Adapt and Adapt-Then-Combine diffusion algorithms based on RLS algorithm are derived shortly by minimising the mixed-node least square-based criterion for distributed estimation over the adaptive network. The mixed-node cost function is described and illustrated briefly. Experimental results depict that these proposed algorithms is able to achieve the fast convergence better than the conventional algorithms.
dc.identifier.doi10.1109/ieecon53204.2022.9741678
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/18731
dc.publisher2022 International Electrical Engineering Congress (iEECON)
dc.subjectAdvanced Adaptive Filtering Techniques
dc.subjectBlind Source Separation Techniques
dc.subjectSpeech and Audio Processing
dc.titleDiffusion Mixed-Node Recursive Least Square-based Algorithm over Adaptive Network
dc.typeArticle

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