• Journal of the Korea Convergence Society
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• v.8 no.11
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• pp.103-108
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• 2017

In the ubiquitous environment, there has been a problem of transmitting data from various sensors at a long distance. Especially, in the process of integrating data arriving at different locations, data having different property values of data or having some loss in data had to be processed. This paper present a method to analyze such data. The core of this method is to define an objective function suitable for the problem and to develop an algorithm that can optimize this objective function. The objective function is used by modifying the OCS function. MFA (Mean Field Annealing), which was able to process only binary data, is extended to be applicable to fields with continuous values. It is called CMFA and used as an optimization algorithm.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.5 s.335
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• pp.39-46
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• 2005

It is well known the fact that turbo codes has better performance as the number of iteration and the interleaver size increases in the AWGN channel environment. However, as the number of iteration and the interleaver size are increased, it is required much delay and computation for iterative decoding. Therefore, it is important to devise an efficient criterion to stop the iteration process and prevent unnecessary computations and decoding delay. In this paper, it proposes the efficient iterative decoding stop criterion using the absolute mean value of LLR difference. It is verifying that the proposal iterative decoding stop criterion can be reduced the average iterative decoding number compared to conventional schemes with a negligible degradation of the error performance.

• Journal of Broadcast Engineering
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• v.21 no.3
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• pp.425-435
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• 2016

In this paper, we propose a classification model by analyzing raw material images recorded using a color CCD camera to automatically classify good and defective agricultural products such as rice, coffee, and green tea, and raw materials. The current classifying agricultural products mainly depends on visual selection by skilled laborers. However, classification ability may drop owing to repeated labor for a long period of time. To resolve the problems of existing human dependant commercial products, we propose a vision based automatic raw material classification combining mean shift clustering and stepwise region merging algorithm. In this paper, the image is divided into N cluster regions by applying the mean-shift clustering algorithm to the foreground map image. Second, the representative regions among the N cluster regions are selected and stepwise region-merging method is applied to integrate similar cluster regions by comparing both color and positional proximity to neighboring regions. The merged raw material objects thereby are expressed in a 2D color distribution of RG, GB, and BR. Third, a threshold is used to detect good and defective products based on color distribution ellipse for merged material objects. From the results of carrying out an experiment with diverse raw material images using the proposed method, less artificial manipulation by the user is required compared to existing clustering and commercial methods, and classification accuracy on raw materials is improved.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.01a
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• pp.243-244
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• 2020

본 논문에서는 SIM(Soft Island Model)을 통해 소집단 정보를 이동시키기 위한 KSDE라고 하는 수많은 전략을 제안한다. 먼저, 전체 모집단은 k- 평균 군집 알고리즘에 의해 k 개의 하위 모집단으로 분리된다. 둘째, 소집단에 돌연변이 조작을 수행하기 위해 전략 풀에서 돌연변이 전략을 무작위로 선택한다. 마지막으로, 이 알고리즘의 모집단 다양성을 개선하기 위해 하위 집단 정보가 SIM을 통해 마이그레이션 된다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.10C
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• pp.1007-1012
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• 2003

In order to accelerate the convergence speed of the conventional BP algorithm, constrained optimization techniques are applied to the BP algorithm. First, the noise-constrained least mean square algorithm and the zero noise-constrained LMS algorithm are applied (designated the NCBP and ZNCBP algorithms, respectively). These methods involve an important assumption: the filter or the receiver in the NCBP algorithm must know the noise variance. By means of extension and generalization of these algorithms, the authors derive an adaptive error-constrained BP algorithm, in which the error variance is estimated. This is achieved by modifying the error function of the conventional BP algorithm using Lagrangian multipliers. The convergence speeds of the proposed algorithms are 20 to 30 times faster than those of the conventional BP algorithm, and are faster than or almost the same as that achieved with a conventional linear adaptive filter using an LMS algorithm.

• Journal of Navigation and Port Research
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• v.28 no.3
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• pp.185-191
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• 2004

The mean and Clustering are important methods of data mining, which is now widely applied to various multi-attributes problem However, feature weighting and feature selection are important in those methods bemuse features may differ in importance and such differences need to be considered in data mining with various multiful-attributes problem. In addition, in the event of arithmetic mean, which is inadequate to figure out the most fitted result for structure of evaluation with attributes that there are weighted and ranked. Moreover, it is hard to catch hold of a specific character for assume the form of user's group. In this paper. we propose a dispersion mean algorithm for evaluation of similarity measure based on the geometrical figure. In addition, it is applied to mean classified by user's group. One of the key issues to be considered in evaluation of the similarity measure is how to achieve objectiveness that it is not change over an item ranking in evaluation process.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.501-504
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• 2005

블록 정합 기법(block matching algorithm, BMA) 중에서 가장 널리 알려진 3 단계 탐색(three-step search, 3SS) 알고리즘은 큰 움직임 추정에 적합하지만 고정된 탐색 점으로 인하여 작은 움직임 추정에는 계산 면에서 낭비가 심하고 탐색이 잘못될 경우가 대부분이다. 한편, 효율적인 3 단계 탐색(efficient three-step search, E3SS)은 중앙-편중된 움직임 추정을 작은 다이아몬드 탐색(small diamond search, SDS) 알고리즘으로 보완하여 예측성과 탐색 속도를 향상시킨 알고리즘이다. 본 논문에서는 탐색 초기 단계에서 탐색 점을 최적 배치하고 E3SS 의 SDS 알고리즘을 변형시킨 탐색 알고리즘을 제안한다. 실험 결과는 제안된 탐색 알고리즘이 E3SS 와 비교하여 평균 22% 정도 계산량을 감소시키면서도 MSE(Mean Square Error)의 성능 저하를 거의 보이지 않는 것으로 나타난다.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2006.06a
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• pp.67-72
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• 2006

적응신호처리 분야에서 LMS(Least Mean Square) 알고리즘은 수식이 간단하고, 적은 계산 량으로 인해 널리 사용되고 있지만, 시간영역의 적응알고리즘은 입력신호의 고유치 분포 폭이 넓게 분포할 때는 수렴속도가 느려지는 단점이 있다. 본 논문에서는 적응 신호처리의 수렴속도를 향상 시키고 복잡한 계산 량을 줄이는 새로운 fast running FIR 필터 구조를 제안한다. 그리고 제안한 알고리즘을 가변스텝 사이즈 웨이블렛 기반 적응 알고리즘에 적용한다. 실제로 합성 음성을 사용하여 적응 잡음 제거기에 적용하여 컴퓨터 시뮬레이션을 통해 제안한 알고리즘과 기존 알고리즘과의 성능을 비교한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.358-359
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• 2018

In this paper, opencv and android studio are used to distinguish between objects ahead of the blind. When the movement is detected in a positive direction in connection with the camera of the smartphone, the user is informed that the part of the camera is being rabelified and continues to track using the mean shift algorithm. A C ++ program based on OpenCV-based was used for real-time motion observation and the application will be produced by android studio. As a result of the study, objects that move with Labeling are identified and the box area is specified using the mean shift algorithm to move the box along with the object to track objects in real time.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.4
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• pp.427-432
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• 2010

To reduce the outage probability and to increase the transmission capacity, the importance of repeaters in cellular systems is increasing. But a RF(Radio Frequency) repeater has a problem that the output of the transmit antenna is partially feedback to the receive antenna, which is feedback interference. In this paper, we proposed adaptive Sign-Sign LMS(Least Mean Square) algorithm using correlations for the performance enhancement of RF repeater. The weight vector is updated by using sign of input signal and error signal to the least squared error of the conventional algorithms. When compared with the conventional method, the proposed canceller achieves the maximum 10 dB performance gain in terms of the MSE(Mean Square Error).