• ETRI Journal
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• v.39 no.6
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• pp.782-793
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• 2017

This paper considers the use of the Partial Transmit Sequence (PTS) technique to reduce the Peak-to-Average Power Ratio (PAPR) of an Orthogonal Frequency Division Multiplexing signal in wireless communication systems. Search complexity is very high in the traditional PTS scheme because it involves an extensive random search over all combinations of allowed phase vectors, and it increases exponentially with the number of phase vectors. In this paper, a suboptimal metaheuristic algorithm for phase optimization based on an improved harmony search (IHS) is applied to explore the optimal combination of phase vectors that provides improved performance compared with existing evolutionary algorithms such as the harmony search algorithm and firefly algorithm. IHS enhances the accuracy and convergence rate of the conventional algorithms with very few parameters to adjust. Simulation results show that an improved harmony search-based PTS algorithm can achieve a significant reduction in PAPR using a simple network structure compared with conventional algorithms.

• Structural Engineering and Mechanics
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• v.29 no.4
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• pp.391-410
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• 2008

In this article, a harmony search algorithm is presented for optimum design of steel frame structures. Harmony search is a meta-heuristic search method which has been developed recently. It is based on the analogy between the performance process of natural music and searching for solutions of optimization problems. The design algorithms obtain minimum weight frames by selecting suitable sections from a standard set of steel sections such as American Institute of Steel Construction (AISC) wide-flange (W) shapes. Stress constraints of AISC Load and Resistance Factor Design (LRFD) and AISC Allowable Stress Design (ASD) specifications, maximum (lateral displacement) and interstorey drift constraints, and also size constraint for columns were imposed on frames. The results of harmony search algorithm were compared to those of the other optimization algorithms such as genetic algorithm, optimality criterion and simulated annealing for two planar and two space frame structures taken from the literature. The comparisons showed that the harmony search algorithm yielded lighter designs for the design examples presented.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.433-439
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• 2019

Artificial bee colony algorithm is a strong global search algorithm which exhibits excellent exploration ability. The conventional ABC algorithm adopts employed bees, onlooker bees and scouts to cooperate with each other. However, its one dimension and greedy search strategy causes slow convergence speed. To enhance its performance, in this paper, we abandon the greedy selection method and propose an artificial bee colony algorithm with special division and intellective search (ABCIS). For the purpose of higher food source research efficiency, different search strategies are adopted with different employed bees and onlooker bees. Experimental results on a series of benchmarks algorithms demonstrate its effectiveness.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1097-1100
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• 1999

Due to the significant computation of full search in motion estimation, extensive research in fast motion estimation algorithms has been carried out. However, most of the algorithms have the degradation in predicted images compared with the full search algorithm. To reduce an amount of significant computation while keeping the same prediction quality of the full search, we propose a fast block-matching algorithm based on gradient magnitude of reference block without any degradation of predicted image. By using Taylor series expansion, we show that the block matching errors between reference block and candidate block are proportional to the gradient magnitude of matching block. With the derived result, we propose fast full search algorithm with adaptively determined scan direction in the block matching. Experimentally, our proposed algorithm is very efficient in terms of computational speedup and has the smallest computation among all the conventional full search algorithms. Therefore, our algorithm is useful in VLSI implementation of video encoder requiring real-time application.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.8
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• pp.81-95
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• 1996

In this paper, we propose a motio estiamtion algorithm using low-resolution quantization to reduce the computation of the full search algorithm. The proposed algorithm consists of the low-resolution search which determins the candidate motion vectors by comparing the low-resolution image and the full-resolution search which determines the motion vector by comparing the full-resolution image on the positions of the candidate motion vectors. The low-resolution image is generated by subtracting each pixel value in the reference block or the search window by the mean of the reference block, and by quantizing it is 2-bit resolution. The candidate motion vectors are determined by counting the number of pixels in the reference block whose quantized codes are unmatched to those in the search window. Simulation results show that the required computational cost of the proposed algorithm is reduced to 1/12 of the full search algorithm while its performance degradation is 0.03~0.12 dB.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.156-161
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• 1997

In this thesis, based on Genetic Algorithm, a new route search algorithm is presented to search an optimal route between the origin and the destination in intelligent route guidance systems in order to minimize the route traveling time. The proposed algorithm is effectively employed to complex road networks which have diverse turn constrains, time-delay constraints due to cross signals, and stochastic traffic volume. The algorithm is also shown to significantly promote search efficiency by changing the population size of path individuals that exist in each generation through the concept of age and lifetime to each path individual. A virtual road-traffic network with various turn constraints and traffic volume is simulated, where the suggested algorithm promptly produces not only an optimal route to minimize the route cost but also the estimated travel time for any pair of the origin and the destination, while effectively avoiding turn constraints and traffic jam.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.3
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• pp.71-79
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• 1998

This paper introduces a new optimization algorithm which is combined with genetic algorithm and random tabu search method. Genetic algorithm is a random search algorithm which can find the global optimum without converging local optimum. And tabu search method is a very fast search method in convergent speed. The optimizing ability and convergent characteristics of a new combined optimization algorithm is identified by using a test function which have many local optimums and an optimum allocation of pipe support. The caculation results are compared with the existing genetic algorithm.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.1
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• pp.57-65
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• 2004

In the block matching algorithm, search patterns of different shapes or sizes and the distribution of motion vectors have a large impact on both the searching speed and the image quality. In this paper, we propose a new fast block matching algorithm using the unit-diamond search pattern and the flat-hexagon search pattern. Our algorithm first finds the motion vectors that are close to the center of search window using the unit-diamond search pattern, and then fastly finds the other motion vectors that are not close to the center of search window using the flat-hexagon search pattern. Through experiments, compared with the hexagon-based search algorithm(HEXBS), the proposed unit-diamond and flat-hexagonal pattern search algorithm(UDFHS) improves as high as 11∼51% in terms of average number of search point per motion vector estimation and improves about 0.05∼0.74㏈ in terms of PSNR(Peak Signal to Noise Ratio).

• Journal of Broadcast Engineering
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• v.12 no.3
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• pp.278-288
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• 2007

We propose the fast full search algorithm that reduces the computational load of the block matching algorithm which is used for a motion estimation in the video coding. Since the conventional spiral search method starts searching at the center of the search window and then moves search point to estimate the motion vector pixel by pixel, it is good for the slow motion picture. However we proposed the efficient motion estimation method which is good for the fast and slow motion picture. Firstly, when finding the initial threshold value, we use the expanded predictor that can approximately calculate minimum threshold value. The proposed algorithm estimates the motion in the new search order after partitioning the search window and adapt the directional search order in the re-divided search window. At the result, we can check that the proposed algorithm reduces the computational load 94% in average compared to the conventional spiral full search algorithm without any loss of image quality.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.183-186
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• 2000

Motion estimation technique has been used to increase video compression rates in motion video applications. One of the important algorithms to implement the motion estimation technique is search algorithm. Among many search algorithms, the H.263 adopted the Nearest Neighbors algorithm for fast search. In this paper, motion estimation block for the Nearest Neighbors algorithm is designed on FPGA and coded using VHDL and simulated under the Xilinx foundation environments. In the experiment results, we verified that the algorithm was properly designed and performed on the Xilinx FPGA(XCV300Q240)