• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2001년도 봄 학술발표논문집 Vol.28 No.1 (A)
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• pp.22-24
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• 2001

슈퍼스칼라 프로세서에서는 분기 명령의 결과 지연으로 명령의 공급이 중단되는 것을 방지하고 지속적인 파이프라인 처리를 위해서 분기의 결과를 미리 예측하여 명령을 폐치하고 있다. 본 논문에서는 심플스칼라 툴 셋을 사용하여 슈퍼스칼라 프로세서에서 사용되는 대표적인 동적 분기예측 방법 시뮬레이션 환경을 구축한다. 동적 분기예측 방법으로 분기 타겟버퍼(Branch Target Buffer, BTB) 상에서 분기명령의 자기 히스토리에 근거한 BTB 방식과 이전 분기명령의 히스토리와의 상관관계를 고려한 Gshare 분기예측기를 적용 구현한다. 심플스칼라 시뮬레이터에 SPEC95 벤치마크 프로그램을 실행시켜 디자인 파라미터 변화에 따른 분기 예측기의 예측정확도를 실험한다. 또한 BTB와 Gshare 분기예측기를 VHDL로 구현하고 Synopsys 툴을 이용하여 시뮬레이션 및 합성 과정을 거쳐 게이트 크기와 파워 소모량을 측정한다.

• 대한전기학회논문지
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• 제40권4호
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• pp.382-393
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• 1991

A DPCM system employing a median predictor, which is called the predictive median-DPCM(PM-DPCM), is proposed. An interesting observation that in PM-DPCM transmission errors are often isolated and not propagated over the reconstructed signal is made, and is analyzed deterministically and statistically. In addition, it is shown that the decoder of the PM-DPCM is always a stable system. In addition, it is shown that the decoder of the PM-DPCM is always a stable system. In order to examine the performance characteristics of PM-DPCM, it is applied to real images. The results indicate that reconstructed images through the PM-DPCM can be better than those through thestandadrd DPCM when transmission errors occur, and that under noise-free conditions the PM-DPCM performs like the standard DPCM.

• 대한전기학회논문지:전력기술부문A
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• 제55권11호
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• pp.485-491
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• 2006

In this paper, we study the problem of model selection for Support Vector Machine(SVM) predictor for short-term load forecasting. The model selection amounts to tuning SVM parameters, such as the cost coefficient C and kernel parameters and so on, in order to maximize the prediction performance of SVM. We propose that Cross-Validation method can be used as a model selection algorithm for SVM-based load forecasting technique. Through the various experiments on several data sets, we found that the difference between the prediction error of SVM using Cross-Validation and that of ideal SVM is less than 5%. This shows that SVM parameters for load forecasting can be efficiently tuned by using Cross-Validation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 D
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• pp.2801-2803
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• 2003

This paper describes a technique for human sensibility evaluation using personality-group templates of EEG(electroencephalogram). 10-channel EEGs of 5 extroverts and 5 introverts are collected in comfortable seat, uncomfortable seat and relaxed state. After preprocessing of EEG, the linear predictor coefficients are extracted and used as feature parameters. A neural network based sensibility classifier is designed and the output of the neural network is assumed as the sensibility index. Multiple templates of two personality-groups are stored and the most similar template can be selected by the proposed method. The proposed method showed the better performance than our previous results which have used ungrouped templates.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2010년도 춘계학술대회
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• pp.839-842
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• 2010

본 논문에서는 핸즈프리 전화통신를 위한 반향 및 잡음제거구조를 제안하다. 제안하는 구조는 주변 잡음이 많을 때 반향 경로 추정 성능이 우수한 개선된 AP 알고리즘을 적응 알고리즘으로 사용하고 비동시 통화구간에서 잔여반향신호를 선형예측하여 백색화시킨다. 컴퓨터 시뮬레이션을 통해 제안하는 방법이 AIC(acoustic interference cancellation) 측면에서 우수함을 보인다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.528-530
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• 2003

We present here, some of the studies carried for estimation of rainfall over land and oceanic regions in and around South Korea. We use active and passive microwave measurements from TRMM ? TMI and Precipitation Radar (PR) respectively during a typhoon even named ? RUSA that took place during 30 Aug. 2002. We have followed due approach by Yao at. all (2002) and examined the performance of their algorithm using two main predictor variable, named as Scattering Index (SI) and Polarization Corrected Brightness Temperature (PCT) while using TMI data. The rainfall fnus estimated using PST and SI shows some Underestimation as compared to the 2A25 rainfall products from the PR in common area of overlap. A larger database thus would be used in future. To establish a new rain rate algorithm over Korean region based on the present case study.

• Ocean Science Journal
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• 제40권4호
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• pp.201-208
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• 2005

An accurate particle tracking method for a finite difference method model is developed using a constant acceleration method. Being assumed constant temporal and spatial gradients, the new method permits temporal-spatial variability of particle velocity. Test results in a solid rotating flow show that the new method has second-order accuracy. The performance of the new method is compared with that of other methods; the first-order Euler forward method, and the second-order Euler predictor-corrector method. The new method is the most efficient method among the three. It is more accurate and efficient than the other two.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2010년도 한국컴퓨터종합학술대회논문집 Vol.37 No.1(C)
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• pp.345-348
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• 2010

본 논문에서는 Isomap을 통해 기상 정보에서 특징을 추출하여, 보다 향상된 오존 경보 예측시스템의 구현을 제안한다. 큰 흐름은 전처리 과정과 특징 추출 과정 및 후처리 과정을 통해 정제한 데이터를, 기계 학습에 널리 사용되고 있는 SVM (Support Vector Machine) 등의 분류기로 오존 경보에 대한 예측을 하여 성능을 측정한다. 또한, 압축된 데이터를 분석하여 원 데이터에서의 중요한 특징들이 무엇이었는지를 분석하였다. 분류기의 실험 결과, 기후 데이터에서의 특징 추출은 제안된 Isomap 방법이 PCA 방법에 비해 성능이 우수한 것을 알 수 있었으며, 원래 데이터를 분류한 결과에 비해서는 15~35%정도가 향상되었다. 그리고 실험에 사용된 72가지의 Feature들 중, Tb, WSa, WSp 의 정보가 오존 경보 예측에 주요한 요인 인 것으로 분석되었다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.201-203
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• 2004

We present here, some of the studies carried for estimation of rainfall over land and oceanic regions in and around South Korea. We use active and passive microwave measurements from TRMM - TMI and Precipitation Radar (PR) respectively during a typhoon even named - RUSA that took place during 30 Aug. 2002. We have followed due approach by Yao at. all (2002) and examined the performance of their algorithm using two main predictor variable, named as Scattering Index (SI) and Polarization Corrected Brightness Temperature (PCT) while using TMI data. The rainfall rate estimated using PCT and SI shows some under-estimation as compared to the AWS rainfall products from the PR in common area of overlap. A larger database thus would be used in future. To establish a new rain rate algorithm over Korean region based on the present case study.

• 전자공학회논문지B
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• 제30B권12호
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• pp.12-20
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• 1993

In a conventional adaptive echo canceller, an ADF(Adaptive Digital Filter) with TDL(Tapped-Delay Line) structure modelling the echo path uses the LMS(Least Mean Square) algorithm to compute the coefficients, and NET detector using energy comparison method prevents the ADF to update the coefficients during the periods of the NET signal presence. The convergence speed of the LMS algorithm depends on the eigenvalue spread ratio of the reference signal and NET detector using the energy comparison method yields poor detection performance if the magnitude of the NET signal is small. This paper presents a new adaptive echo canceller which uses the pre-whitening filter to improve the convergence speed of the LMS algorithm. The pre-whitening filter is realized by using a low-order lattice predictor. Also, a new NET signal detection algorithm is presented, where the start point of the NET signal is detected by computing the cross-correlation coefficient between the primary input and the ADF output while the end point is detected by using the energy comparison method. The simulation results show that the convergence speed of the proposed adaptive echo canceller is faster than that of the conventional echo canceller and the cross-correlation coefficient yields more accurate detection of the start point of the NET signal.