Wiangtong, Theerayod

Preferred name

Alternative Name

Wiangtong, T.

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School of Engineering

theerayod.wi@kmitl.ac.th

Now showing 1 - 10 of 13

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A heuristic approach for scheduling in heterogeneous distributed embedded systems
(2020-02-01)
Prongnuch, Sethakarn
;
Sitjongsataporn, Suchada
;
Wiangtong, Theerayod
This paper presents a heuristic approach for workflow scheduling in heterogeneous distributed embedded system (HDES). A genetic algorithm (GA) and ant colony optimization (ACO) modified with the greedy algorithm introduced to the system contains multiple heterogeneous embedded machines (HEMs) working as a cluster. Users can remotely access and utilize their computational power. The communications on different types of buses are taken into account to find an optimal solution. New meta-heuristic information based on forwarding dependency is proposed to build probability for ACO to generate task priorities. Besides, a greedy algorithm for machine allocation is incorporated to complete task scheduling. Experiments based on random task graphs running in the HEM cluster demonstrate the effectiveness of the modified greedy ant colony optimization algorithm which outperforms the others by 33% more result quality.
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Stochastic behaviour analysis of adaptive averaging step-size sign normalised hammerstein spline adaptive filtering
(2021-01-01)
Wiangtong, Theerayod
;
Prongnuch, Sethakarn
;
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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An Adaptive inverse Square-root Affine Projection Sign Algorithm based on QR-Decomposition
(2020-10-14)
Sitjongsataporn, Suchada
;
Prongnuch, Sethakarn
;
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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Simplified Set-Membership Affine Projection Least Mean Fourth Algorithm
(2022-01-01)
Sitjongsataporn, Suchada
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Prongnuch, Sethakarn
;
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 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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Performance Evaluation of Heterogeneous Cluster for Satellite Data Processing
(2019-12-01)
Prongnuch, Sethakarn
;
Sitjongsataporn, Suchada
;
Wiangtong, Theerayod
This paper presents the performance evaluation of heterogeneous cluster for satellite data processing. The proposed system consists of a master and eight slaves of the heterogeneous system connected to a start-network switch. The metric performance is used for satellite data processing algorithm. For the performance evaluation, the overall processing time is 102.85 seconds. Additionally, comparisons with the related work show better than 1.6 times of processing time compared with the previous work.
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Diffusion Mixed-Node Recursive Least Square-based Algorithm over Adaptive Network
(2022-01-01)
Sitjongsataporn, Suchada
;
Prongnuch, Sethakarn
;
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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Hammerstein Spline Adaptive Filtering based on Normalised Least Mean Square Algorithm
(2019-12-01)
Prongnuch, Sethakarn
;
Sitjongsataporn, Suchada
;
Wiangtong, Theerayod
This paper proposes a normalised least mean square algorithm based on Hammerstein spline adaptive filtering. A nonlinear Hammerstein adaptive filters consists of memory-less function modified during learning and the spline control point is automatically controlled by gradient-based method. Simulation results demonstrate that the proposed algorithm exhibits more robust performance compared with the conventional spline adaptive filtering algorithms.
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Diffusion inverse square-root recursive least square-based algorithm with adaptive network
(2021-05-19)
Sitjongsataporn, Suchada
;
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 recursive least squares algorithm based on triangular decomposition
(2023-10-01)
Prongnuch, Sethakarn
;
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.

Wiangtong, Theerayod

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