• Title/Summary/Keyword: search algorithm

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Fast Cell Search Algorithm using Polarization Code Modulation(PCM) in WCDMA Systems (WCDMA 시스템에서 극성 변조를 이용한 빠른 셀 탐색 알고리즘)

  • Bae Sung-Oh;Lim Jae-Sung
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.8B
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    • pp.809-818
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    • 2002
  • In this paper, we propose a fast cell search algorithm keeping compatible with the standard cell search algorithm of the WCDMA system. The proposed algorithm can acquire the synchronization of slot and frame times, and the code group identification using only one synchronization channel while the standard algorithm employs two synchronization channels called P-SCH and S-SCH. The proposed synchronization channel structure is the same as the P-SCH structure of the WCDMA system. However, the P-SCH is modulated with a specific polarization code, which is one element of new code group codes. The proposed algorithm can reduce both the BS' transmission power and the complexity of receiver as compared with the conventional one since only on synchronization channel is used. It is shown through the computer simulation that the proposed algorithm yields a significant improvement in terms of cell search time compared with the standard especially in low SNR environments.

PC Cluster based Parallel Adaptive Evolutionary Algorithm for Service Restoration of Distribution Systems

  • Mun, Kyeong-Jun;Lee, Hwa-Seok;Park, June-Ho;Kim, Hyung-Su;Hwang, Gi-Hyun
    • Journal of Electrical Engineering and Technology
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    • v.1 no.4
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    • pp.435-447
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    • 2006
  • This paper presents an application of the parallel Adaptive Evolutionary Algorithm (AEA) to search an optimal solution of the service restoration in electric power distribution systems, which is a discrete optimization problem. The main objective of service restoration is, when a fault or overload occurs, to restore as much load as possible by transferring the de-energized load in the out of service area via network reconfiguration to the appropriate adjacent feeders at minimum operational cost without violating operating constraints. This problem has many constraints and it is very difficult to find the optimal solution because of its numerous local minima. In this investigation, a parallel AEA was developed for the service restoration of the distribution systems. In parallel AEA, a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner are used in order to combine the merits of two different evolutionary algorithms: the global search capability of the GA and the local search capability of the ES. In the reproduction procedure, proportions of the population by GA and ES are adaptively modulated according to the fitness. After AEA operations, the best solutions of AEA processors are transferred to the neighboring processors. For parallel computing, a PC cluster system consisting of 8 PCs was developed. Each PC employs the 2 GHz Pentium IV CPU and is connected with others through switch based fast Ethernet. To show the validity of the proposed method, the developed algorithm has been tested with a practical distribution system in Korea. From the simulation results, the proposed method found the optimal service restoration strategy. The obtained results were the same as that of the explicit exhaustive search method. Also, it is found that the proposed algorithm is efficient and robust for service restoration of distribution systems in terms of solution quality, speedup, efficiency, and computation time.

Fast Motion Estimation Algorithm via Optimal Candidate for Each Step (단계별 최적후보를 통한 고속 움직임 예측 알고리즘)

  • Kim, Jong-Nam;Moon, Kwang-Seok
    • Journal of the Institute of Convergence Signal Processing
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    • v.18 no.2
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    • pp.62-67
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    • 2017
  • In this paper, we propose a fast motion estimation algorithm which is important in performance of video encoding. Even though so many fast algorithms for motion estimation have been published due to tremendous computational amount of full search algorithm, efforts for reducing computations of motion estimation still remain. In the paper, we propose an algorithm that reduces unnecessary computations only, while keeping prediction quality the same as that of the full search. The proposed algorithm does not calculate block matching error for each candidate directly to find motion vectors but divides the calculation procedure into several steps and calculates partial sum of block errors for candidates with high priority. By doing that, we can find the minimum error point early and get the enhancement of calculation speed by reducing unnecessary computations. The proposed algorithm uses smaller computations than conventional fast search algorithms with the same prediction quality as the full search algorithm.

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A Tabu Search Algorithm for Node Reprogramming in Wireless Sensor Networks (무선 센서 네트워크에서 노드 재프로그래밍을 위한 타부 서치 알고리즘)

  • Jang, Kil-woong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.5
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    • pp.596-603
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    • 2019
  • A reprogramming operation is necessary to update the software code of the node to change or update the functionality of the deployed node in wireless sensor networks. This paper proposes an optimization algorithm that minimizes the transmission energy of a node for the purpose of reprogramming a node in wireless sensor networks. We also design an algorithm that keeps energy consumption of all nodes balanced in order to maintain the lifetime of the network. In this paper, we propose a Tabu search algorithm with a new neighborhood generation method for minimizing transmission energy and energy consumption in wireless sensor networks with many nodes. The proposed algorithm is designed to obtain optimal results within a reasonable execution time. The performance of the proposed Tabu search algorithm was evaluated in terms of the node's transmission energy, remaining energy, and algorithm execution time. The performance evaluation results showed better performance than the previous methods.

Improved Route Search Method Through the Operation Process of the Genetic Algorithm (유전 알고리즘의 연산처리를 통한 개선된 경로 탐색 기법)

  • Ji, Hong-il;Moon, Seok-hwan
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.05a
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    • pp.632-635
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    • 2015
  • Proposal algorithm in this thesis introduced cells, units of router group, for distributed processing of previous genetic algorithm. This thesis presented ways to reduce search delay time of overall network through cell-based genetic algorithm. As a result of performance analysis comparing with existing genetic algorithm through experiments, the proposal algorithm was found superior in terms of costs and delay time. Furthermore, time for routing an alternative path was reduced in proposal algorithm, in case that a network was damaged in existing optimal path algorithm, Dijkstra algorithm, and the proposal algorithm was designed to route an alternative path faster than Dijkstra algorithm, as it has a 2nd shortest path in cells of the damaged network. The study showed that the proposal algorithm can support routing of alternative path, if Dijkstra algorithm is damaged in a network.

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Fast Video Motion Estimation Algorithm Based on Motion Speed and Multiple Initial Center Points Prediction (모션 속도와 다중 초기 중심점 예측에 기반한 빠른 비디오 모션 추정 알고리즘)

  • Peng, Sha-Hu;Saipullah, Khairul Muzzammil;Yun, Byung-Choon;Kim, Deok-Hwan
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.12
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    • pp.1219-1223
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    • 2010
  • This paper proposes a fast motion estimation algorithm based on motion speed and multiple initial center points. The proposed method predicts initial search points by means of the spatio-temporal neighboring motion vectors. A dynamic search pattern based on the motion speed and the predicted initial center points is proposed to quickly obtain the motion vector. Due to the usage of the spatio-temporal information and the dynamic search pattern, the proposed method greatly accelerates the search speed while keeping a good predicted image quality. Experimental results show that the proposed method has a good predicted image quality in terms of PSNR with less searching time comparing with the Full Search, New Three-Step Search, and Four-Step Search.

A Study on Terrain Surface Modeling and Polygon-Searching Algorithms (지표면 모델링 및 폴리건 검색기법에 관한 연구)

  • 공지영;강현주;윤석준
    • Proceedings of the Korea Society for Simulation Conference
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    • 2002.11a
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    • pp.163-170
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    • 2002
  • Terrain surfaces have to be modeled in very detail and wheel-surface contacting geometry must be well defined in order to obtain proper ground-reaction and friction forces for realistic simulation of off-road vehicles. Delaunay triangulation is one of the most widely used methods in modeling 3-dimensional terrain surfaces, and T-search is a relevant algorithm for searching resulting triangular polygons. The T-search method searches polygons in successive order and may not allow real-time computation of off-road vehicle dynamics if the terrain is modeled with many polygons, depending on the computer performance used in the simulation. In order to accelerate the searching speed of T-search, a terrain database of triangular polygons is modeled in multi-levels by adopting the LOD (Level of Detail) method used in realtime computer graphics. Simulation results show that the new LOD search is effective in shortening the required computing time. The LOD search can be even further accelerated by introducing an NN (Neural Network) algorithm, in the cases where a appropriate range of moving paths can be predicted by cultual information of the simulated terrain, such as lakes, houses, etc.. Numerical tests show that LOD-NN search almost double the speed of the original T-search.

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A Study on the Target Search Logic in the ASW Decision Support System (대잠전 의사결정지원 시스템에서 표적 탐색 논리 연구)

  • Cho, Sung-Jin;Choi, Bong-Wan;Jeon, Jae-Hyo
    • Journal of the Korea Institute of Military Science and Technology
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    • v.13 no.5
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    • pp.824-830
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    • 2010
  • It is not easy job to find a underwater target using sonar system in the ASW operations. Many researchers have tried to solve anti-submarine search problem aiming to maximize the probability of detection under limited searching conditions. The classical 'Search Theory' deals with search allocation problem and search path problem. In both problems, the main issue is to prioritize the searching cells in a searching area. The number of possible searching path that is combination of the consecutive searching cells increases rapidly by exponential function in the case that the number of searching cells or searchers increases. The more searching path we consider, the longer time we calculate. In this study, an effective algorithm that can maximize the probability of detection in shorter computation time is presented. We show the presented algorithm is quicker method than previous algorithms to solve search problem through the comparison of the CPU computation time.

Vocabulary Recognition Retrieval Optimized System using MLHF Model (MLHF 모델을 적용한 어휘 인식 탐색 최적화 시스템)

  • Ahn, Chan-Shik;Oh, Sang-Yeob
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.10
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    • pp.217-223
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    • 2009
  • Vocabulary recognition system of Mobile terminal is executed statistical method for vocabulary recognition and used statistical grammar recognition system using N-gram. If limit arithmetic processing capacity in memory of vocabulary to grow then vocabulary recognition algorithm complicated and need a large scale search space and many processing time on account of impossible to process. This study suggest vocabulary recognition optimize using MLHF System. MLHF separate acoustic search and lexical search system using FLaVoR. Acoustic search feature vector of speech signal extract using HMM, lexical search recognition execution using Levenshtein distance algorithm. System performance as a result of represent vocabulary dependence recognition rate of 98.63%, vocabulary independence recognition rate of 97.91%, represent recognition speed of 1.61 second.

Fast Full Search Block Matching Algorithm Using The Search Region Subsampling and The Difference of Adjacent Pixels (탐색 영역 부표본화 및 이웃 화소간의 차를 이용한 고속 전역 탐색 블록 정합 알고리듬)

  • Cheong, Won-Sik;Lee, Bub-Ki;Lee, Kyeong-Hwan;Choi, Jung-Hyun;Kim, Kyeong-Kyu;Kim, Duk-Gyoo;Lee, Kuhn-Il
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.11
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    • pp.102-111
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    • 1999
  • In this paper, we propose a fast full search block matching algorithm using the search region subsampling and the difference of adjacent pixels in current block. In the proposed algorithm, we calculate the lower bound of mean absolute difference (MAD) at each search point using the MAD value of neighbor search point and the difference of adjacent pixels in current block. After that, we perform block matching process only at the search points that need block matching process using the lower bound of MAD at each search point. To calculate the lower bound of MAD at each search point, we need the MAD value of neighbor search point. Therefore, the search points are subsampled at the factor of 4 and the MAD value at the subsampled search points are calculated by the block matching process. And then, the lower bound of MAD at the rest search points are calculated using the MAD value of the neighbor subsampled search point and the difference of adjacent pixels in current block. Finally, we discard the search points that have the lower bound of MAD value exceed the reference MAD which is the minimum MAD value of the MAD values at the subsampled search points and we perform the block matching process only at the search points that need block matching process. By doing so, we can reduce the computation complexity drastically while the motion compensated error performance is kept the same as that of full search block matching algorithm (FSBMA). The experimental results show that the proposed method has a much lower computational complexity than that of FSBMA while the motion compensated error performance of the proposed method is kept same as that of FSBMA.

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