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Diffusion recursive least squares algorithm based on triangular decomposition
(2023-10-01)
Prongnuch, Sethakarn
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Sitjongsataporn, Suchada
;
Wiangtong, Theerayod
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.
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Diffusion Spline Adaptive Filtering with Adaptive Step-size Normalised Least Mean Square Algorithm
(2023-01-01)
Sitjongsataporn, Suchada
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Prongnuch, Sethakarn
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Wiangtong, Theerayod
Diffusion adaptation on spline adaptive filtering (SAF)is presented with combine-then-adapt (CTA) strategy for each node. SAF consists of an adaptive linear filtering and a spline interpolation function. Normalised least mean square algorithm is furnished in the adaptive linear filtering part. An adaptive averaging step-size mechanism is applied for both tap-weight vector of linear and nonlinear filtering parts to provide the fast convergence with low computation complexity. Statistical results testify that the proposed diffusion algorithm is able to provide promising and competitive results to the conventional diffusion strategy algorithm.
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Diffusion Mixed-Node Recursive Least Square-based Algorithm over Adaptive Network
(2022-01-01)
Sitjongsataporn, Suchada
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Prongnuch, Sethakarn
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Wiangtong, Theerayod
This 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.
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Diffusion Affine Projection Sign Least Mean Fourth Algorithm for Distributed Estimation
(2022-01-01)
Sitjongsataporn, Suchada
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Prongnuch, Sethakarn
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Wiangtong, Theerayod
The problem of distributed estimation is considered for distributed network. A diffusion model on adaptive affine projection sign algorithm based on least mean fourth algorithm is introduced according to an Adapt-Then-Combine (ATC) design for the distributed framework. Least mean fourth (LMF) algorithm is defined by taking the fourth power of error to against the non-Gaussian environment. An adaptive affine projection sign algorithm based on LMF algorithm is proposed firstly. Then, an ATC diffusion model on adaptive affine projection sign algorithm based on LMF algorithm is presented in terms of the low complexity of sign approach with the order of adaptation and combination, named as ATC-DAPS-LMF. Numerical simulations verify that the proposed algorithm can perform significantly to the conventional affine projection sign algorithm.
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Simplified Set-Membership Affine Projection Least Mean Fourth Algorithm
(2022-01-01)
Sitjongsataporn, Suchada
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Prongnuch, Sethakarn
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Wiangtong, Theerayod
A simplified forms of adaptive set-membership affine projection based on least mean fourth algorithm is proposed. Least mean fourth (LMF) algorithm is defined by taking the fourth power of error to against the non-Gaussian environment. A set-membership adaptive filtering is described firstly. Then, an affine projection algorithm is based on LMF algorithm. A simplified set-membership affine projection algorithm based on LMF is introduced. Adaptive threshold parameter and learning rate are presented for improvement of convergence rate. Numerical simulations show that the proposed algorithm can provide significantly to the conventional affine projection algorithm.
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Diffusion inverse square-root recursive least square-based algorithm with adaptive network
(2021-05-19)
Sitjongsataporn, Suchada
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Prongnuch, Sethakarn
;
Wiangtong, Theerayod
In 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.
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Diffusion Affine Projection Sign Algorithm based on QR-Decomposition
(2021-03-10)
Sitjongsataporn, Suchada
;
Prongnuch, Sethakarn
;
Wiangtong, Theerayod
In this paper, an Adapt-Then-Combine diffusion strategy on affine projection sign algorithm is presented. Based on the QR-decomposition method, the modified inverse autocorrelation matrix is shortly brief to decrease the computational complexity. The Adapt-Then-Combine diffusion strategy is applied on the low complexity of sign algorithm version of inverse square-root affine projection algorithm including with the adaptation and combination steps. By applying an idea of diffusion adaptation algorithm, we derive a diffused version of an affine projection sign algorithm based on QR-Decomposition, denoted as DiQR-APSA. Experimental results show that the proposed DiQR-APSA can achieve the good performance in comparison with the standard affine projection sign algorithm.
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Stochastic behaviour analysis of adaptive averaging step-size sign normalised hammerstein spline adaptive filtering
(2021-01-01)
Wiangtong, Theerayod
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Prongnuch, Sethakarn
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Sitjongsataporn, Suchada
We introduce a sign algorithm based on the normalised least mean square with Hammerstein adaptive filtering using adaptive averaging step-size mechanism, which is derived by the minimised absolute a posteriori squared error. To improve the performance by reducing computational complexity, we suggest an adaptive averaging using energy of errors to update step-size variant. The analysis of convergence behaviour and mean square performance are derived. Experimental results reveal that the proposed algorithm can perform better than the least mean square approach based on the Hammerstein model of adaptive filtering.
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Qualitative Precipitation Estimation from Satellite Data Based on Distributed Domain-Specific Architecture
(2021-01-01)
Prongnuch, Sethakarn
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Wiangtong, Theerayod
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Sitjongsataporn, Suchada
This paper presents the qualitative precipitation estimation (QPE) based on data from the Himawari satellite and distributed-domain specific architecture. The QPE process consists of receiving and managing the raw data from the satellite every 10 minutes and calculating the rain-temperature relationship. The aim of this research is to decrease the QPE processing time by using distributed domain-specific architecture (DDSA), with 9 small computing boards are connected to a gigabit switch. Instead of using a high-performance PC, this distributed embedded system is also suitable for processing interval data receiving from the satellite every 10 minutes. The experimental results show that the proposed fast-satellite data processing algorithm is optimal for QPE processing on the DDSA platform, requiring 115.53 seconds processing time and low power consumption.
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An Adaptive inverse Square-root Affine Projection Sign Algorithm based on QR-Decomposition
(2020-10-14)
Sitjongsataporn, Suchada
;
Prongnuch, Sethakarn
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Wiangtong, Theerayod
In this paper, we present an adaptive averaging step-size inverse square-root affine projection sign algorithm. Based on the QR-decomposition method, we derive the modified inverse autocorrelation matrix in order to reduce the complexity of inverse matrix, which a criterion is based on the proposed algorithm with the sign error. Adaptive averaging step-size mechanism is used for the fast adaptation. Convergence analysis in form of a posteriori error is presented. Simulation results show that the proposed algorithm can obtain clearly the better performance compared with the conventional affine projection algorithm.

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