• 전자공학회논문지C
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• 제34C권6호
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• pp.11-21
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• 1997

The delay models for CMOS invertr presented so far predicted the delay time quite accurately whens input transition-time is very small. But the problem that the accuracy is inclined to decrease becomes apparent as input transition tiem increases. In this paper, a delay model for CMOS inverter is presented, which accuractely predicts the delay time even though input transition-time increases. To inverter must be included in modeling process because the main reason of inaccuracy as input transition tiem is the leakage current through the complementary MOS. For efficient modeling, this paper first models the MOSes with simple I-V charcteristic, with which both the pMOS and the nMOS are considered easily in calculating the inverter delay times. This resulting model needs few parameters and re-models each MOS effectively and simply evaluates output voltage to predict delay time, delay values obtained from this effectively and simply evaluates output voltage to predict delay time, delay values obtained from this model have been found to be within about 5% error rate of the SPICE results. The calculation time to predict the delay time with the model from this paper has the speed of more than 70times as fast as to the SPICE.

• JSTS:Journal of Semiconductor Technology and Science
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• 제10권1호
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• pp.20-27
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• 2010

Modeling is essential to simulate the operation of integrated circuit (IC) before its fabrication. Seeing a large number of Metal-Oxide-Silicon Field-Effect-Transistor (MOSFET) models available, it has become important to understand them and compare them for their pros and cons. The task becomes equally difficult when the complexity of these models becomes very high. The paper reviews the mainstream models with their physical relevance and their comparisons. Major short-channel and quantum effects in the models are outlined. Emphasis is set upon the latest compact models like BSIM, MOS Models 9/11, EKV, SP etc.

• 전자공학회논문지D
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• 제34D권12호
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• pp.31-38
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• 1997

A new CAD-compatible non-quasi-static (NQS) MOS transient model is presented. A new type of weighted residual method, the collcoatin method, is adopted to obtian an approximate ordinary differntial equation from the continuity eqation. Contrasting to the conventional NQS models, the new model can directly include the variatin of the depletion charge and the derived transient current sare expressed with only physically meaningful variables. The new model predicts transient behaviors reasonably well in the calculation including cutoff regions where the depletion charge rapidly changes.

• 한국콘텐츠학회논문지
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• 제5권4호
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• pp.254-264
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• 2005

본 논문에서는 기존의 문제점들을 극복하기 위한 개선된 E-Model을 제안하였다. 새로운 모델은 버스트 패킷손실과 최신효과를 적용하여 VoIP 품질 측정의 정확도를 높일 수 있다. 개선된 E-Model은 길버트 모델에 의해 생성된 버스트 패킷 손실에 따라 NR(Network R) 값과 UR(User R) 값을 측정한다. 기존 모델들인 MOS, PESQ, E-Model과 비교하여 시뮬레이션을 수행하였으며, 실험 결과 개선된 E-Model이 기존 모델들보다 정확하고 신뢰성 있음이 증명되었다.

• 전기학회논문지
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• 제61권11호
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• pp.1682-1688
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• 2012

This paper introduces a GP(Genetic Programming) based robust technique for temperature compensation in short-range prediction. Development of an efficient MOS(Model Output Statistics) is necessary to correct systematic errors of the model, because forecast models do not reliably determine weather conditions. Most of MOS use a linear regression to compensate a prediction model, therefore it is hard to manage an irregular nature of prediction. In order to solve the problem, a nonlinear and symbolic regression method using GP is suggested. The purpose of this study is to evaluate the accuracy of the estimation by a GP based nonlinear MOS for 3 days temperatures in Korean regions. This method is then compared to the UM model and has shown superior results. The training period of 2007-2009 summer is used, and the data of 2010 summer is adopted for verification.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.150-150
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• 2018

The Numerical Weather Prediction (NWP) models provide information for weather forecasts. The highly nonlinear and complex interactions in the atmosphere are simplified in meteorological models through approximations and parameterization. Therefore, the simplifications may lead to biases and errors in model results. Although the models have improved over time, the biased outputs of these models are still a matter of concern in meteorological and hydrological studies. Thus, bias removal is an essential step prior to using outputs of atmospheric models. The main idea of statistical bias correction methods is to develop a statistical relationship between modeled and observed variables over the same historical period. The Model Output Statistics (MOS) would be desirable to better match the real time forecast data with observation records. Statistical post-processing methods relate model outputs to the observed values at the sites of interest. In this study three methods are used to remove the possible biases of the real-time outputs of the Weather Research and Forecast (WRF) model in Imjin basin (North and South Korea). The post-processing techniques include the Linear Regression (LR), Linear Scaling (LS) and Power Scaling (PS) methods. The MOS techniques used in this study include three main steps: preprocessing of the historical data in training set, development of the equations, and application of the equations for the validation set. The expected results show the accuracy improvement of the real-time forecast data before and after bias correction. The comparison of the different methods will clarify the best method for the purpose of the forecast skill enhancement in a real-time case study.

• JSTS:Journal of Semiconductor Technology and Science
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• 제13권3호
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• pp.213-223
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• 2013

A unified channel thermal noise model valid in all operation regions is presented for short channel MOS transistors. It is based on smooth interpolation between weak and strong inversion models and consistent physical model including velocity saturation, channel length modulation, and carrier heating. From testing for noise benchmark and comparing with published noise data, it is shown that the proposed noise model could be useful in simulating the MOSFET channel thermal noise in all operation regions.

• Communications for Statistical Applications and Methods
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• 제13권2호
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• pp.369-378
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• 2006

This Study focuses on the binary forecast of occurrence of heavy snow in Honam area based on the MOS(model output statistic) method. For our study daily amount of snow cover at 17 stations during the cold season (November to March) in 2001 to 2005 and Corresponding 45 RDAPS outputs are used. Logistic regression model and neural networks are applied to predict the probability of occurrence of Heavy snow. Based on the distribution of estimated probabilities, optimal thresholds are determined via true shill score. According to the results of comparison the logistic regression model is recommended.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 추계학술대회
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• pp.795-797
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• 2009

Voice over IP(VoIP) 서비스가 많이 사용함에 따라 각종 Network Model 기반의 VoIP 서비스 기술이 제시 되어 있다. VoIP 서비스에 대한 품질 평가 척도인 Mean Opinion Score(MOS)[1]가 보장하려면 안정된 Network 환경을 지원해야 한다. 하지만 Mobile Ad-Hoc Network(MANET) 기반의 VoIP 서비스인 VoMANET은 MANET의 불안정성이 가져온 Packet Loss와 Delay 때문에 좋은 MOS를 얻을 수가 없다. 본 논문에서는 NS-2(Network Simulation-2)[2]를 이용하여 VoMANET을 분석하였다. 그리고 Network Topology 크기와 노드의 밀도를 조절하여 받은 다른 결과를 참조하고 VoMANET 성능의 개선 방안을 제시한다.

• 말소리와 음성과학
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• 제16권1호
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• pp.67-76
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• 2024

최근 음성합성(text-to-speech, TTS) 기술의 발전은 합성음의 음질을 크게 향상하였으며, 사람의 음성에 가까운 합성음을 생성할 수 있는 수준에 이르렀다. 특히, 다양한 음성 특성과 개인화된 음성을 제공하는 TTS 모델은 AI(artificial intelligence) 튜터, 광고, 비디오 더빙과 같은 분야에서 널리 활용되고 있다. 따라서 본 논문은 훈련 중 보지 않은 화자의 발화를 사용하여 음성을 합성함으로써 음향적 다양성을 보장하고 개인화된 음성을 제공하는 원샷 다화자 음성합성 시스템을 제안했다. 이 제안 모델은 FastSpeech2 음향 모델과 HiFi-GAN 보코더로 구성된 TTS 모델에 RawNet3 기반 화자 인코더를 결합한 구조이다. 화자 인코더는 목표 음성에서 화자의 음색이 담긴 임베딩을 추출하는 역할을 한다. 본 논문에서는 영어 원샷 다화자 음성합성 모델뿐만 아니라 한국어 원샷 다화자 음성합성 모델도 구현하였다. 제안한 모델로 합성한 음성의 자연성과 화자 유사도를 평가하기 위해 객관적인 평가 지표와 주관적인 평가 지표를 사용하였다. 주관적 평가에서, 제안한 한국어 원샷 다화자 음성합성 모델의 NMOS(naturalness mean opinion score)는 3.36점이고 SMOS(similarity MOS)는 3.16점이었다. 객관적 평가에서, 제안한 영어 원샷 다화자 음성합성 모델과 한국어 원샷 다화자 음성합성 모델의 P-MOS(prediction MOS)는 각각 2.54점과 3.74점이었다. 이러한 결과는 제안 모델이 화자 유사도와 자연성 두 측면 모두에서 비교 모델들보다 성능이 향상되었음을 의미한다.