• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.15-22
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• 2023

An Ant Colony Optimization Algorithm(ACO) is one of the frequently used algorithms to solve the Traveling Salesman Problem(TSP). Since the ACO searches for the optimal value by updating the pheromone, it is difficult to consider the distance between the nodes and other variables other than the amount of the pheromone. In this study, fuzzy logic is added to ACO, which can help in making decision with multiple variables. The improved algorithm improves computation complexity and increases computation time when other variables besides distance and pheromone are added. Therefore, using the algorithm improved by the fuzzy logic, it is possible to solve TSP with many variables accurately and quickly. Existing ACO have been applied only to pheromone as a criterion for decision making, and other variables are excluded. However, when applying the fuzzy logic, it is possible to apply the algorithm to various situations because it is easy to judge which way is safe and fast by not only searching for the road but also adding other variables such as accident risk and road congestion. Adding a variable to an existing algorithm, it takes a long time to calculate each corresponding variable. However, when the improved algorithm is used, the result of calculating the fuzzy logic reduces the computation time to obtain the optimum value.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.2
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• pp.69-76
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• 2010

This paper proposed a new fast multi-reference frame motion estimation algorithm. The proposed algorithm reduces search areas of motion estimation using a linear relation of motion vector with distance of each reference frame. New algorithm executes full search area motion estimation in reference frame 0 and reference frame 1. After that, search areas in reference frame 2, reference frame 3 and reference frame 4 are minimized by distance of each reference frame and results of motion estimation in reference frame 0 and reference frame 1. The proposed algorithm does not use a threshold value which is obstacle of hardware implementation and processing time schedule. Also, it reduced computation quantity of multi-reference motion estimation. Hardware implementation of multi-reference frame motion estimation is possible by these features. Simulation results show that PSNR drop and bitrate increase of proposed algorithm are lower than those of previous fast multi-reference frame motion estimation algorithm The number of computation of new algorithm is reduced 52.5% and quality of result is negligible when compared with full search area motion estimation which has 5 reference frames.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.11_12
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• pp.692-704
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• 2005

With the improvement of computer hardware, GPUs(Graphics Processor Units) have tremendous memory bandwidth and computation power. This leads GPUs to use in general purpose computation. Especially, GPU implementation of compute-intensive physics based simulations is actively studied. In the solution of differential equations which are base of physics simulations, tridiagonal matrix systems occur repeatedly by finite-difference approximation. From the point of view of physics based simulations, fast solution of tridiagonal matrix system is important research field. We propose a fast GPU implementation for the solution of tridiagonal matrix systems. In this paper, we implement the cyclic reduction(also known as odd-even reduction) algorithm which is a popular choice for vector processors. We obtained a considerable performance improvement for solving tridiagonal matrix systems over Thomas method and conjugate gradient method. Thomas method is well known as a method for solving tridiagonal matrix systems on CPU and conjugate gradient method has shown good results on GPU. We experimented our proposed method by applying it to heat conduction, advection-diffusion, and shallow water simulations. The results of these simulations have shown a remarkable performance of over 35 frame-per-second on the 1024x1024 grid.

• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.157-168
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• 2016

In image processing and computer vision fields, mean squared error (MSE) has popularly been used as an objective metric in image quality optimization problems due to its desirable mathematical properties such as metricability, differentiability and convexity. However, as known that MSE is not highly correlated with perceived visual quality, much effort has been made to develop new image quality assessment (IQA) metrics having both the desirable mathematical properties aforementioned and high prediction performances for subjective visual quality scores. Although recent IQA metrics having the desirable mathematical properties have shown to give some promising results in prediction performance for visual quality scores, they also have high computation complexities. In order to alleviate this problem, we propose a new fast IQA metric using a simple Laplace operator. Since the Laplace operator used in our IQA metric can not only effectively mimic operations of receptive fields in retina for luminance stimulus but also be simply computed, our IQA metric can yield both very fast processing speed and high prediction performance. In order to verify the effectiveness of the proposed IQA metric, our method is compared to some state-of-the-art IQA metrics. The experimental results showed that the proposed IQA metric has the fastest running speed compared the IQA methods except MSE under comparison. Moreover, our IQA metric achieves the best prediction performance for subjective image quality scores among the state-of-the-art IQA metrics under test.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.6
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• pp.881-888
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• 1993

A new stabilizing algorithm for the fast transversal filter (FTF) which is known to exhibit a very unstable behavior, due basically to the accumulation in two different ways, we define a emasure counting these at each step of the algorithm in order to reduce the roundoff error. It has been shown that required amount of computation for the proposed algorithm is linearly increased as the order of equalizer and that stability is improved in comparison with the other existing algorithm. It has been shown that the proposed algorithm exhibits a good performance using computer simulation of adaptive equalization for multipath fading channel in urban mobile radio environment.

• Journal of The Korean Association of Information Education
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• v.15 no.3
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• pp.517-524
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• 2011

This paper presents a fast blind deconvolution method that produces a deblurring result from a single image in only a few seconds. The high speed of our method is enabled by considering the Discrete Fourier Transform (DFT), and its relation to filtering and convolution, and fast computation of Moore-Penrose inverse matrix. How can we predict the behavior of an arbitrary filter, or even more to the point design a filter to achieve certain specifications. The idea is to study the frequency response of the filter. This concept leads to an useful convolution formula. A Matlab implementation of our method usually takes less than one minute to deblur an image of moderate size, while the deblurring quality is comparable.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.9 s.112
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• pp.895-899
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• 2006

A compact representation of Green function is proposed by applying the discrete wavelet concept in the k-domain, which can be used for the acceleration of scattered field calculations in integral equation methods. Since the representation of Green function is very compact in the joint spatio-spectral domain, it can be effectively utilized in the fast computation of radiation integral of electromagnetic problems. A mathematical expression of Green function based on the discrete wavelet concept is derived and its characteristics are discussed.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.12 no.6
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• pp.972-982
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• 2001

FMM(Fast Multipole Method) is suitable numerical method for radar cross section calculation of arbitrary large conducting bodies due to reduction of computation time. The accuracy of the numerical results, however, can influenced by selection of grouping method and segment length, in particular, far the case that cross section of the scatter is of the narrow width elliptical type. So, we describe the FMM method which can be deal effectively with such difficulties for both TM and TE polarization case. In order to check the present method the results are compared with those obtained by Method of Moments.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.387-392
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• 2002

This paper presents a new scheme of neural network controller to improve the robustuous of robot manipulator using digital signal processors. Digital signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of variables. Digital version of most advanced control algorithms can be defined as sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of their prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. During past decade it was proposed the well-established theorys for the adaptive control of linear systems, but there exists relatively little general theory for the adaptive control of nonlinear systems. Perforating of the proposed controller is illustrated. This paper describes a new approach to the design of adaptive controller and implementation of real-time control for assembling robotic manipulator using digital signal processor. Digital signal processors used in implementing real time adaptive control algorithm are TMS320C50 series made in TI'Co..

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.134-139
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• 2001

This paper presents a new scheme of neural network controller to improve the robustuous of robot manipulator using digital signal processors. Digital signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of variables. Digital version of most advanced control algorithms can be defined as sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of their prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. During past decade it was proposed the well-established theorys for the adaptive control of linear systems, but there exists relatively little general theory for the adaptive control of nonlinear systems. Perforating of the proposed controller is illustrated. This paper describes a new approach to the design of adaptive controller and implementation of real-time control for assembling robotic manipulator using digital signal processor. Digital signal processors used in implementing real time adaptive control algorithm are TMS320C50 series made in TI'Co..