• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.8C
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• pp.756-763
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• 2009

The Least Mean Square (LMS) algorithm is often used to restore signal corrupted by additive noise. A major defect of this algorithm is that the excess Mean Square Error (EMSE) increases linearly according to speech signal power. This result reduces the efficiency of performance significantly due to the large EMSE around the optimum value. Choosing a small step size solves this defect but causes a slow rate of convergence. The step size must be optimized to satisfy a fast rate of convergence and minimize EMSE. In this paper, the Instantaneous Gain Control (IGC) algorithm is proposed to deal with the situation as it exists in speech signals. Simulations were carried out using a real speech signal combined with Gaussian white noise. Results demonstrate the superiority of the proposed IGC algorithm over the LMS algorithm in rate of convergence, noise reduction and EMSE.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2009.11a
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• pp.511-514
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• 2009

In this study, the combustion characteristics of hybrid rocket fuel with tapered grain port were studied. The regression rate was increased about 17.5% by using the convergence port shape fuel. On the other hand, in case of divergence port shape fuel, any notable difference of regression rate was not observed when compared with regression rate of the cylindrical port shape fuel. Also, in case of convergence port shape fuel, characteristic velocity efficiency was increased. From these results, one can notice that convergence port shape of hybrid rocket fuel can be effective configuration in terms of improvement of combustion efficiency and performance.

• Journal of Korea Multimedia Society
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• v.6 no.5
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• pp.788-796
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• 2003

This paper proposes using dynamic momentum for squential learning method. Using The dynamic momentum improves convergence speed and performance by the variable momentum, also can identify it in the RMSE(root mean squared error). The proposed method is reflected using variable momentum according to current state. While static momentum is equally influenced on the whole, dynamic momentum algorithm can control the convergence rate and performance. According to the variable change of momentum by training. Unlike former classification and regression problems, this paper confirms both performance and regression rate of the dynamic momentum. Using RMSE(root mean square error ), which is one of the regression methods. The proposed dynamic momentum has been applied to the kernel adatron and kernel relaxation as the new sequential learning method of support vector machine presented recently. In order to show the efficiency of the proposed algorithm, SONAR data, the neural network classifier standard evaluation data, are used. The simulation result using the dynamic momentum has a better convergence rate, performance and RMSE than those using the static moment, respectively.

• Korea Trade Review
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• v.43 no.1
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• pp.47-67
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• 2018

This study analyzed whether the poverty level among Asian countries has converged, by using data for the 'globalization period'. In particular, we analyzed the impact of trade on convergence by quantitative analysis using two indices; the head count ratio (H) and the human development index (HDI). The σ-convergence measurement and β-convergence measurement method, commonly used in the field of economic growth, are used for the analysis method. Results show that poverty rates have declined on average during the analysis period and there has been an increase in HDI. It seems that there has been improvement regarding poverty. However, this trend is only an indication of the average trend of Asian countries as a whole. As for the convergence between countries, which is the focus of this study, the HDI index shows the converges among countries while the H index does not show significant convergence among countries. It is also difficult to determine that trade has a statistically significant impact on the poverty rate convergence. However, in the case of HDI convergence, trade has contributed to increasing the convergence rates. This results might show that globalization does not guarantee the convergence among countries, and thus, we need to have additional policy in order to reduce the poverty.

• Journal of the Korean Society of Propulsion Engineers
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• v.15 no.2
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• pp.8-14
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• 2011

In this paper, the combustion characteristics of hybrid rocket fuel with tapered grain port were investigated experimentally. The charging efficiency of convergent and divergent port shape fuel with $1^{\circ}$ taper angle was 6.8% higher than that of cylindrical port shape fuel. The regression rate was increased about 17.5% by using the convergent port shape fuel. On the other hand, in case of divergent port shape fuel, no notable difference of regression rate was observed when compared to that of the cylindrical port shape fuel. In the case of convergent port shape fuel, characteristic velocity and its efficiency were notably increased with respect to cylindrical port fuel. It was found that convergent port shape of hybrid rocket fuel can lead to a better option compared to the conventional cylindrical port in terms of combustion efficiency and performance improvement.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.927-930
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• 2001

본 논문에서는 웨이블렛 변환 알고리듬을 이용 한 음향반향 제거 기법을 제안하였다. 일반적으로 LMS 알고리듬은 간단하지만 그 수렴특성이 고유치 분포율과 탭 수에 의해 결정되는 단점이 있고 MDF (multidelay filter)를 이용한 적응 알고리듬은 블록단위로 수행되는 LMS를 수렴속도 측면에서 보완해주지만 긴 차수일때는 FFT에 비례하여 연산량이 늘어나는 단점이 있다. 본 논문은 웨이블렛의 직교성을 이용한 변환 적응 알고리듬을 음향반향 제거기에 도입하여 그 성능을 비교·평가하였다. 모의실험을 통해 시간영역 LMS, MDF 알고리듬과 비교하여 제안한 알고리듬의 수렴성능이 우수함을 보였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.11
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• pp.2459-2469
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• 1997

In this paper, the multi-stage radius-directed algorithm is applied to fractionally spaced equalizers which are insensitive to the sampling timing-phase. these equalizers exhibit good convergence characeristics when compared to fractionally spaced blind equalizers using conventional blind algorithms. Also, multi-model fractionally spaced blind equalizers, which use multiple symbol spaced blind equalizers that operate independently, converge faster than conventional fractionally spaced blind equalizers.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2005.11a
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• pp.109-112
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• 2005

ATSC 지상파 DTV 시스템에서 심볼 타이밍 동기 성능 개선을 위한 알고리즘을 제안한다. 일반적으로 심볼 타이밍 동기를 위해 사용되는 가드너 방법은 다중 경로 페이딩 환경에서 성능이 좋지만 지터에 의해 성능 열화가 발생한다. 지터량는 루프 필터 대역폭이 작을수록 작아지지만, 수렴속도는 느려지게 된다. 수렴속도는 빠르면서 수렴 후 지터량를 감소시키기 위해 일정시간마다 루프필터의 출력 값을 평균하고 이 평균값을 이용하여 옵셋량을 추정한 후 추정된 옵셋의 변화율에 따라 루프 필터의 대역폭을 줄여 지터의 크기를 줄이는 알고리즘을 제안한다.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.313-315
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• 2002

본 논문에서는 학습 중 모멘트를 동적으로 조절하여 수련속도와 학습 성능을 향상시키는 동적모멘트를 제안하고 회귀방법으로 동적모멘트의 성능을 재확인한다. 제안된 학습방법은 기존의 정적모멘트와는 달리 수렴 정도에 따라 현재의 학습에 과거의 학습률을 단리 반영하는 방법으로 다른 학습법에 비해 보다 유연한 초평면을 갖으며 수렴에 이르는 시간이 오래 걸리는 KR(Kernel Relaxation)에 적용하여 그 성능을 확인한다. 본 논문에서 사용한 회귀방법은 RMS 오류율을 사용하였으며 제안된 학습방법인 동적모멘트를 SVM(support vector machine)의 순차 학습방법 중 최근 발표된 KR에 적용하여 RMS 오류율을 확인하였다. 실험의 공정성을 위해 신경망 분류기 표준평가데이터인 SONAR 데이터를 사용하였으며 실험 결과 동적모멘트를 이용한 회귀율이 정적모멘트를 이용한 방법보다 향상되었음을 확인하였다.

• Journal of the Korean Data and Information Science Society
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• v.9 no.1
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• pp.19-27
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• 1998

We considered the bandwidth selection method which has asymptotic optimal convergence rate $n^{-1/2}$ in kernel regression function estimation. For the proposed bandwidth selection, we considered Mean Averaged Squared Error as a performance criterion and its Taylor expansion to the fourth order. Then we estimate the bandwidth which minimizes the estimated approximate value of MASE. Finally we show the relative convergence rate between optimal bandwidth and proposed bandwidth.