Wiangtong, Theerayod

Preferred name

Alternative Name

Wiangtong, T.

Main Affiliation

School of Engineering

theerayod.wi@kmitl.ac.th

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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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FPGA based-IC design for inverter with vector modulation technique
(2000-01-01)
Wiangtong, Theerayod
;
Sangchai, Worranart
;
Lumyong, Pichit
This paper presents an application of an ALTERA FPGA Device, in the FLEX10K family, producing Pulse Width Modulation (PWM) signals with the vector modulation technique for an IGBT inverter. Using a single FPGA chip for the practical implementation of the modulator, rather than a system consisting of microprocessor and external memory, has many advantages including less use of power and space, short design time, greater speed and reliability. The designed circuit can generate PWM signals at many different frequencies, and also, the input values used to adjust output signal may be obtained through either a 4×4 keypad or microprocessor port.
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Performance of Hammerstein Spline Adaptive Filtering Based on Fair Cost Function for Denoising Electrocardiogram Signals
(2025-12-01)
Sitjongsataporn, Suchada
;
Wiangtong, Theerayod
This paper proposes a simplified adaptive filtering approach using a Hammerstein function and the spline interpolation based on a Fair cost function for denoising electrocardiogram (ECG) signals. The use of linear filters in real-world applications has many limitations. Adaptive nonlinear filtering is a key development in tackling the challenge of discovering the specific characteristics of biomimetic systems for each person in order to eliminate unwanted signals. A biomimetic system refers to a system that mimics certain biological processes or characteristics of the human body, in this case, the individual features of a person’s cardiac signals (ECG). Here, the adaptive nonlinear filter is designed to cope with ECG variations and remove unwanted noise more effectively. The objective of this paper is to explore an individual biomedical filter based on adaptive nonlinear filtering for denoising the corrupted ECG signal. The Hammerstein spline adaptive filter (HSAF) architecture consists of two structural blocks: a nonlinear block connected to a linear one. In order to make a smooth convergence, the Fair cost function is introduced for convergence enhancement. The affine projection algorithm (APA) based on the Fair cost function is used to denoise the contaminated ECG signals, and also provides fast convergence. The MIT-BIH 12-lead database is used as the source of ECG biomedical signals contaminated by random noises modelled by Cauchy distribution. Experimental results show that the estimation error of the proposed HSAF–APA–Fair algorithm, based on the Fair cost function, can be reduced when compared with the conventional least mean square-based algorithm for denoising ECG signals.
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Performance analysis of cascade spline adaptive filtering based on normalized orthogonal gradient adaptive algorithm
(2024-12-01)
Wiangtong, Theerayod
;
Sitjongsataporn, Suchada
In this paper, the cascade architecture of spline adaptive filtering (CSAF) for nonlinear systems is presented with the normalized version of orthogonal gradient adaptive (NOGA) algorithm. Spline adaptive filtering comprises a sandwich of the first linear adaptive filtering (LAF) and nonlinear adaptive look-up table. In this cascading architecture, SAF is connected to the second LAF. NOGA is considered as the fast convergence applied by stochastic gradient-based approach. Convergence properties of the proposed NOGA-CSAF algorithm in terms of instantaneous errors can be derived by using Taylor series expansion. Experimental results demonstrate the effectiveness of proposed NOGA-CSAF algorithm using the mean square error scheme. It clearly outperforms the traditional least mean square algorithm on CSAF model in the nonlinear identification system.
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FPGA-based IC design for 3-phase PWM inverter with optimized space vector modulation schemes
(2000-01-01)
Sangchai, Worranart
;
Wiangtong, Theerayod
;
Lumyong, Pichit
This paper presents a novel idea to integrate three of the Space Vector Modulation (SVM) schemes, including the alternating zero sequence, the symmetric sequence and the bus clamped, in only a single FPGA chip which provides many advantages. Flexibility, reliability and very compact system are obviously obtained from this designed chip. Moreover, faster design and verification time, design change without penalty are also the benefits resulted in FPGA-Based IC design. The optimized SVM schemes, frequencies and programmable deadtime that used to adjust output signals are obtained through either 4×4 keypad or microprocessor port.
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Analysis of normalized orthogonal gradient adaptive algorithm based on spline adaptive filtering for smart communication technology
(2021-06-02)
Wiangtong, Theerayod
;
Sitjongsataporn, Suchada
This paper presents a general theoretical framework of spline adaptive filtering based on a normalized version of orthogonal gradient adaptive algorithm. A nonlinear spline adaptive filter normally consists of a linear combination with a memory-less function and a spline function for adaptive approach. We explain how the adaptive linear filter and spline control points are derived in a straightforward iterative gradient-based method. In order to improve the convergence characteristics, the normalized version of orthogonal gradient adaptive algorithm is introduced by the orthogonal projection along with the gradient adaptive algorithm. In addition, a simple form of adaptation algorithm is introduced how to obtain a lower bound on the excess mean square error (MSE) in a theoretical basis. Convergence and stability analysis based on the MSE criterion are proven in terms of the excess MSE. Simulation results reveal that the proposed algorithm achieves more robustness compared with the conventional spline adaptive filtering 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.
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Qualitative Precipitation Estimation from Satellite Data Based on Distributed Domain-Specific Architecture
(2021-01-01)
Prongnuch, Sethakarn
;
Wiangtong, Theerayod
;
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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A Low-cost Autonomous Lawn Mower with AI-Based Obstacle Avoidance and GPS Guidance System
(2025-07-01)
Kosri, Thanapon
;
Seekhamharn, Tossawat
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Phoonsrichaiyasit, Phasawut
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Khungpo, Poowadon
;
Sirisuk, Phaophak
This paper presents a cost-effective robotic system capable of manual control via RF remote and autonomous navigation using GPS-based information. The system employs artificial intelligence to dynamically classify and avoid non-grass obstacles, ensuring safe operation in real environments. The prototype integrates affordable hardware including Arduino board, sensors, actuators and Raspberry Pi with lightweight algorithms to balance performance and cost. Experimental validation confirms its ability to follow predefined paths with ±1.5 meters deviation in open area and 90% obstacle avoidance success rate. With a total hardware cost under $200, this prototype highlights feasibility for larger-scale implementation.

Wiangtong, Theerayod

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