Diffusion recursive least squares algorithm based on triangular decomposition

In this paper, diffusion strategies used by QR-decomposition based on recursive least squares algorithm (DQR-RLS) and the sign version of DQR-RLS algorithm (DQR-sRLS) are introduced for distributed networks. In terms of the QR-decomposition method and Cholesky factorization, a modified Kalman vector...

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Vydané v:International journal of electrical and computer engineering (Malacca, Malacca) Ročník 13; číslo 5; s. 5101
Hlavní autori: Prongnuch, Sethakarn, Sitjongsataporn, Suchada, Wiangtong, Theerayod
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: 01.10.2023
ISSN:2088-8708, 2722-2578
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Shrnutí:In this paper, diffusion strategies used by QR-decomposition based on recursive least squares algorithm (DQR-RLS) and the sign version of DQR-RLS algorithm (DQR-sRLS) are introduced for distributed networks. In terms of the QR-decomposition method and Cholesky factorization, a modified Kalman vector is given adaptively with the help of unitary rotation that can decrease the complexity from inverse autocorrelation matrix to vector. According to the diffusion strategies, combine-then-adapt (CTA) and adapt-then-combine (ATC) based on DQR-RLS and DQR-sRLS algorithms are proposed with the combination and adaptation steps. To minimize the cost function, diffused versions of CTA-DQR-RLS, ATC-DQR-RLS, CTA-DQR-sRLS and ATC-DiQR-sRLS algorithms are compared. Simulation results depict that the proposed DQR-RLS-based and DQR-sRLS-based algorithms can clearly achieve the better performance than the standard combine-then-adapt-diffusion RLS (CTA-DRLS) and ATC-DRLS mechanisms.
ISSN:2088-8708
2722-2578
DOI:10.11591/ijece.v13i5.pp5101-5108