• Title/Summary/Keyword: search region

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Hydro-Thermal Optimal Scheduling Using Probabilistic Tabu Search (확률 타부 탐색법을 이용한 수화력 계통의 경제운용에 관한 연구)

  • Kim, Hyeong-Su;Mun, Gyeong-Jun;Park, Jun-Ho
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.51 no.3
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    • pp.153-161
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    • 2002
  • In this paper, we propose a Probabilistic Tabu Search(PTS) method for hydro-thermal scheduling. Hydro scheduling has many constraints and very difficult to solve the optical schedule because it has many local minima. To solve the problem effectively, the proposed method uses two procedures, one is Tabu search procedure that plays a role in local search, and the other is Restarting procedure that enables to diversify its search region. To adjust Parameters such as a reducing rate and initial searching region, search strategy is selected according to its probability after restarting procedure. Dynamic decoding method was also used to restrict a search region and to handle water balance constraints. In order to show the usefulness of the proposed method, the PTS is applied on two cases which have independent or dependent hydro plants and compared to those of other method. The simulation results show it is very efficient and useful algorithm to solve the hydro-thermal scheduling problem.

Past Block Matching Motion Estimation based on Multiple Local Search Using Spatial Temporal Correlation (시공간적 상관성을 이용한 국소 다중 탐색기반 고속 블록정합 움직임 추정)

  • 조영창;남혜영;이태홍
    • Journal of Korea Multimedia Society
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    • v.3 no.4
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    • pp.356-364
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    • 2000
  • Block based fast motion estimation algorithm use the fixed search pattern to reduce the search point, and are based on the assumption that the error in the mean absolute error space monotonically decreases to the global minimum. Therefore, in case of many local minima in a search region we are likely to find local minima instead of the global minimum and highly rely on the initial search points. This situation is evident in the motion boundary. In this paper we define the candidate regions within the search region using the motion information of the neighbor blocks and we propose the multiple local search method (MLSM) which search for the solution throughout the candidate regions to reduce the possibilities of isolation to the local minima. In the MLSM we mark the candidate region in the search point map and we avoid to search the candidate regions already visited to reduce the calculation. In the simulation results the proposed method shows more excellent results than that of other gradient based method especially in the search of motion boundary. Especially, in PSNR the proposed method obtains similar estimate accuracy with the significant reduction of search points to that of full search.

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90$^{\circ}$Rotational Image Retrieval Method Based on Region Classification and Wavelet Transform (영역 분류와 웨이브렛 변환을 이용한 90$^{\circ}$회전된 영상 검색 기법)

  • 이경민;이한정;김미화;황도연;유강수;곽훈성
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.1851-1854
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    • 2003
  • This paper suggests an algorithm which can retrieval images using correlations between the region classification of spatial image and the wavelet transform even though the images are rotated in a ${\pm}$90 degree arc. Owing to this proposed method, it was confirmed from experiments that the search about the whole image is not processed and only a few amount of informations are saved by using the mathematical statistics from the block map and transformed band which is resulted from region classification, and by performing the image search based on these, the improvement of search speed and the efficient search can be done.

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A Fast Block Matching Algorithm Using Mean Absolute Error of Neighbor Search Point and Search Region Reduction (이웃 탐색점에서의 평균 절대치 오차 및 탐색영역 줄임을 이용한 고속 블록 정합 알고리듬)

  • 정원식;이법기;한찬호;권성근;장종국;이건일
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.1B
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    • pp.128-140
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    • 2000
  • In this paper, we propose a fast block matching algorithm using the mean absolute error (MAE) of neighbor search point and search region reduction. The proposed algorithm is composed of two stages. At the first stage,the search region is divided into nonoverlapped 3$\times$3 areas and MAE of the center point of each area iscalculated. The minimum MAE value of all the calculated MAE's is determined as reference MAE. At thesecond stage, because the possibility that final motion vector exist near the position of reference MAE is veryhigh, we use smaller search region than first stage, And, using the MAE of center point of each area, the lowerbound of rest search point of each area is calculated and block matching process is performed only at the searchpoints that the lower bound is smaller than reference MAE. By doing so, we can significantly reduce thecomputational complexity while keep the increasement of motion estimation error small.

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A New Diversity Preserving Evolutionary Programming Technique (다양성을 유지하는 새로운 진화 프로그래밍 기법)

  • 신정환;진성일;최두현
    • Proceedings of the IEEK Conference
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    • 1999.11a
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    • pp.1011-1014
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    • 1999
  • In this paper, a new algorithm has been presented that helps to preserve diversity as well as to enhance the convergence speed of the evolutionary programming. This algorithm is based on the cell partitioning of search region for preserving the diversity. Until now, the greater part of researches is not concerned about preserving the diversity of individuals in a population but improving convergence speed. Although these evolutions are started from multi-point search at the early phase, but at the end those search points are swarming about a one-point, the strong candidate. These evolutions vary from the original idea in some points such as multi-point search. In most case we want to find the only one point of the best solution not several points in the vicinity of that. That is why the cell partitioning of search region has been used. By restricting the search area of each individual, the diversity of individual in solution space is preserved and the convergence speed is enhanced. The efficiency of the proposed algorithm has been verified through benchmark test functions.

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Hydro-Thermal Optimal Scheduling Using Probabilistic Tabu Search (확률 타부 탐색법을 이용한 수화력 계통의 경제운용)

  • Kim, Hyung-Su;Park, June-Ho
    • Proceedings of the KIEE Conference
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    • 2002.11b
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    • pp.76-79
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    • 2002
  • In this paper, we propose a Probabilistic Tabu Search(PTS) method for hydro-thermal scheduling. Hydro scheduling has many constraints and very difficult to solve the optimal schedule because it has many local minima. To solve the problem effectively, the proposed method uses two procedures, one is Tabu search procedure that plays a role in local search, and the other is Restarting procedure that enables to diversify its search region. To adjust parameters such as a reducing rate and initial searching region, search strategy is selected according to its probability after Restarting procedure. In order to show the usefulness of the proposed method, the PTS is applied on two cases which have dependent hydro plants and compared to those of other method. The simulation results show it is very efficient and useful algorithm to solve the hydro-thermal scheduling problem.

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Data Reusable Search Scan Methods for Low Power motion Estimation (저전력 움직임 추정을 위한 데이터 재사용 스캔 방법)

  • Kim, Tae Sun;SunWoo, Myung Hoon
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.9
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    • pp.85-91
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    • 2013
  • This paper proposes the data reusable search scan methods for full search and fast search to implement low power Motion Estimation (ME). The proposed Optimized Sub-region Partitioning (OSP) method which divide search region into several sub-region can reduce the number of the required Reconfigurable Register Array (RRA) by half compared to the existing smart snake scan method for the same data reusability. In addition, the proposed Center Biased Search Scan method (CBSS) for various fast search algorithms can improve the data reusability. The performance comparisons show that the proposed search scan methods can reduce the average redundant data loading about 26.9% and 16.1% compared with the existing rater scan and snake scan methods, respectively. Due to the reduction of memory accesses, the proposed search scan methods are quite suitable for low power and high performance ME implementation.

Motion Search Region Prediction using Neural Network Vector Quantization (신경 회로망 벡터 양자화를 이용한 움직임 탐색 영역의 예측)

  • Ryu, Dae-Hyun;Kim, Jae-Chang
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.1
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    • pp.161-169
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    • 1996
  • This paper presents a new search region prediction method using vector quantization for the motion estimation. We find motion vectors using the full search BMA from two successive frame images first. Then the motion vectors are used for training a codebook. The trained codebook is the predicted search region. We used the unsupervised neural network for VQ encoding and codebook design. A major advantage of formulating VQ as neural networks is that the large number of adaptive training algorithm that are used for neural networks can be applied to VQ. The proposed method reduces the computation and reduce the bits required to represent the motion vectors because of the smaller search points. The computer simulation results show the increased PSNR as compared with the other block matching algorithms.

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Multiple Candidate Region Search Based Fast Block Matching Motion Estimation (다중 후보영역 탐색기반 고속 블록정합 움직임 추정)

  • 조영창;윤정오;이태홍
    • Proceedings of the IEEK Conference
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    • 2000.06d
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    • pp.47-49
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    • 2000
  • In this paper we propose the multiple local search method(MLSM) based on the motion information of the neighbor blocks. In the proposed method motions are estimated from the multiple searches of many candidate local search regions. To reduce the additional search points we avoid to search the same candidate regions previously visited using the distance from the initial search point to the recently found vector points. In the simulation the proposed method shows more excellent results than that of other gradient based method especially in the search of motion boundary.

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The Study on Anti-Submarine Search Pattern of the Surface Ship Considering the Torpedo Countermeasure Tactics (어뢰대항전술 영향을 고려한 수상함의 대잠탐색패턴 연구)

  • Lee, Min-Kyu
    • Journal of the Korea Institute of Military Science and Technology
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    • v.13 no.2
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    • pp.204-210
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    • 2010
  • The tactical effectiveness, which is the result of applying decision-making algorithms to respond a specific situation with weapons and sensors, is required to analyze according to the integrated combat situation, because each situation, which is intimately involved with each other, influences the surface ship to complete missions successfully. However, the tactical effectiveness have been analyzed in separation of each tactical situation due to the complexity of the integrated tactical situation. This paper is originated from the needs for analyzing the anti-submarine search region of the surface ship after it evades the torpedo by operation of the torpedo countermeasure tactics. It also describes simulation results of effectiveness analysis for the search patterns in the search region.