• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
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• pp.493-496
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• 2003

Recently, Ryu et al. proposed a multiple target DOA tracking algorithm, which has good features that it has no data association problem and simple structure. But its performance is seriously degraded in the low signal-to-noise ratio. In this paper, a measurement fusion method is presented based on ML(Maximum Likelihood), and the new DOA tracking algorithm is proposed by incorporating the presented fusion method into Ryu's algorithm. The proposed algorithm has a better tracking performance than that of Ryu's algorithm, and it sustains the good features of Ryu's algorithm.

• 대한임베디드공학회논문지
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• 제12권6호
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• pp.377-384
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• 2017

The scope of the matrix application is so broad that it can not be limited. A typical matrix application area in computer science is image processing. Particularly, radar scanning equipment implemented on a small embedded system requires real-time matrix transposition for image processing, and since its memory size is small, a general matrix transposition algorithm can not be applied. In this case, matrix transposition must be done in disk space, such as flash disk, using a limited memory buffer. In this paper, we analyze and improve a recently published flash disk-based matrix transposition algorithm named as asymmetric sub-matrix transposition algorithm. The performance analysis shows that the asymmetric sub-matrix transposition algorithm has lower performance than the conventional sub-matrix transposition algorithm, but the improved asymmetric sub-matrix transposition algorithm is superior to the sub-matrix transposition algorithm in 13 of the 16 experimental data.

• 한국공작기계학회논문집
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• 제13권3호
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• pp.126-132
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• 2004

This paper proposed trajectory tracking control based on genetic algorithm. Trajectory tracking control scheme are real coding genetic algorithm(RCGA) and back-propagation algorithm(BPA). Control scheme ability experience proposed simulation. Stable tracking control problem of mobile robots have been studied in recent years. These studies have guaranteed stability of controller, but the performance of transient state has not been guaranteed. In some situations, constant gain controller shows overshoots and oscillations. So we introduce better control scheme using real coding genetic algorithm and neural network. Using RCGA, we can find proper gains in several situations and these gains are generalized by neural network. The generalization power of neural network will give proper gain in untrained situation. Performance of proposed controller will verity numerical simulations and the results show better performance than constant gain controller.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2003년도 추계학술발표논문집 (중)
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• pp.1007-1010
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• 2003

Efficient using of web cache is becoming important factor that decide system management efficiency in web-Based system. Cache performance depends heavily on replacement algorithms, which dynamically select a suitable subset of objects for caching in a finite space. However, replacement algorithm on web cache has many differences than traditional replacement algorithm. In this paper, a web-caching algorithm is proposed for efficient operation of web base system. The algorithm is designed based on a divided scope that considered size reference characteristic and heterogeneity on web object. The performance of the algorithm is analyzed with an experiment. With the experiment results, the algorithm is compared with previous replacement algorithms, and its performance is confirmed ith an improvement of response speed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권6호
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• pp.2554-2580
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• 2018

Lenstra-Lenstra-$Lov{\acute{a}}sz$ (LLL) is an effective receiving algorithm for Multiple-Input-Multiple-Output (MIMO) systems, which is believed can achieve full diversity in MIMO detection of fading channels. However, the LLL algorithm features polynomial complexity and shows poor performance in terms of convergence. The reduction of algorithmic complexity and the acceleration of convergence are key problems in optimizing the LLL algorithm. In this paper, a variant of the LLL algorithm, the Hybrid-Fix-and-Round LLL algorithm, which combines both fix and round measurements in the size reduction procedure, is proposed. By utilizing fix operation, the algorithmic procedure is altered and the size reduction procedure is skipped by the hybrid algorithm with significantly higher probability. As a consequence, the simulation results reveal that the Hybrid-Fix-and-Round-LLL algorithm carries a faster rate of convergence compared to the original LLL algorithm, and its algorithmic complexity is at most one order lower than original LLL algorithm in real field. Comparing to other families of LLL algorithm, Hybrid-Fix-and-Round-LLL algorithm can make a better compromise in performance and algorithmic complexity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권12호
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• pp.5785-5804
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• 2019

The information of localization is a fundamental requirement in wireless sensor network (WSN). The method of distance vector-hop (DV-Hop), a range-free localization algorithm, can locate the ordinary nodes by utilizing the connectivity and multi-hop transmission. However, the error of the estimated distance between the beacon nodes and ordinary nodes is too large. In order to enhance the positioning precision of DV-Hop, fast triangle flip bat algorithm, which is based on curve strategy and rank transformation (FTBA-TCR) is proposed. The rank is introduced to directly select individuals in the population of each generation, which arranges all individuals according to their merits and a threshold is set to get the better solution. To test the algorithm performance, the CEC2013 test suite is used to check out the algorithm's performance. Meanwhile, there are four other algorithms are compared with the proposed algorithm. The results show that our algorithm is greater than other algorithms. And this algorithm is used to enhance the performance of DV-Hop algorithm. The results show that the proposed algorithm receives the lower average localization error and the best performance by comparing with the other algorithms.

• 한국전자파학회논문지
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• 제12권3호
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• pp.360-369
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• 2001

본 논문은 동기복조 방식의 그룹단위 직렬 교차 간섭제거(GSCIC; Groupwise serial cross interference cance-llation) 알고리즘을 제안하고, 기존 GBSIC(Groupwise serial block interference cancellation) 알고리즘과 함께 다중경로 페이닝 채널에서 단위 셀 비동기 W-CDMA 시스템 역방향 링크에 적용하여 해석하였다. 그룹단위 직렬 간섭제거 알고리즘(GSIC; Groupwise serial interference cancellation)은 일반적으로 그룹단위 직렬 블록 간섭제거(GSBIC) 알고리즘과 그룹단위 직렬 교차 간섭제거(GSCIC) 알고리즘으로 나눌 수 있다. 본 논문에서는 GSCIC 제안 알고리즘은 기존 GSBIC 알고리즘을 개선한 것이다. 다중 경로 페이딩 채널에서 GSBIC 알고리즘은 감소인자 $R_{f}$에 따라 GSBIC 알고리즘보다 우수한 성능을 얻었고, 직렬 간섭제거 알고리즘과 비슷한 성능을 얻었다. 한편, GSBIC와 GSCIC 알고리즘은 시스템 처리 능력에 따라 그룹 내 사용자 수를 가변하면서 성능을 쉽게 분석할 수 있는 장점을 갖고 있다.

• 대한전자공학회논문지TE
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• 제37권2호
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• pp.54-61
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• 2000

본 논문은 레일레이 페이딩 채널 환경에서 IMT-2000 파일럿 심볼 구조의 W-CDMA 시스템 역방향 링크의 채널 추정에 관한 RLS 적응형 알고리즘 성능을 WMSA(K=1,3)와 Constant gain 방식의 성능과 비교 분석하였다. 본 논문의 모델은 IMT-2000 시스템 규격의 W-CDMA 채널 구조, 변조 및 파일럿 패턴을 이용하였다. 파일럿 심볼 위치의 채널추정은 RLS 적응형 알고리즘을 이용하고 데이터 심볼 위치의 채널 보상은 선형보간으로 수행하였다. RLS 적응형 알고리즘 성능은 저속 페이딩에서 WMSA(K=1,3) 성능과 유사하지만 Constant gain 알고리즘 성능보다는 약간 우수하다. 도플러 주파수 320㎐, BER=2.0×10/sup -2/에서 RLS 적응형 알고리즘 성능이 WMSA(K=1)과 Constant gain 성능에 비해 4㏈의 성능 우위를 보여주고 있으며, WMSA(K=3)의 성능과는 커다란 차이를 보여준다. 따라서 페이딩이 고속화 될수록 RLS 알고리즘 의 성능이 전반적으로 WMSA(K=1,3)와 Constant gain 알고리즘 성능보다 우수함을 확인하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 V
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• pp.2787-2790
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• 2003

In this paper, we predict tracking performance of the multiple hypothesis tracking (MHT) algorithm. The MHT algorithm is known to be an optimal Bayesian approach and is superior to asly other tracking filters because it takes into account the events that the measurements can be originated from new targets and false alarms 3s well as interesting targets. In the MHT algorithm, a number of candidate hypotheses are generated and evaluated later as more data are received. The probability of each candidate hypotheses is approximately evaluated by using the hybrid conditional average approach (HYCA). We performed numerical experiments to show the validity of our performance prediction.

• Journal of information and communication convergence engineering
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• 제6권4호
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• pp.434-438
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• 2008

Massive data are continuously produced with a data rate of over several terabytes every day. These applications need effective clustering algorithms to achieve an overall high performance computation. In this paper, we propose ancestor as cluster center based approach to clustering, the K-means algorithm using ancestor. We modify the K-means algorithm. We present a clustering architecture and a clustering algorithm that minimize of I/Os and show a performance with excellent. In our experimental performance evaluation, we present that our algorithm can improve the I/O speed and the query processing time.