• 대한수학회보
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• 제39권4호
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• pp.705-714
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• 2002

We consider a jump-diffusion model generated by a Levy process for an asset price. We present an error estimate for the option prices between the jump-diffusion model and the Black-scholes model when the former converges weakly to the latter.

• 전자공학회논문지
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• 제50권1호
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• pp.27-33
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• 2013

본 논문에서는 two-way 릴레이 네트워크에서 파일롯(pilot)기반 채널 추정 기법과, 전송시 데이터 심볼과 함께 파일롯 심볼을 전송하는 기법을 제안한다. 채널상태정보(channel state information : CSI)가 없는 경우, destination은 파일롯 심볼을 사용해 채널을 추정한다. 이 시스템에서 릴레이는 파일롯 심볼과 데이터 심볼을 증폭하고 AF(amplify and forward)프로토콜을 사용하여 destination에 전송한다. 릴레이 이득이 고정되어 있어서 릴레이는 채널을 추정할 필요가 없기 때문에 destination이 채널을 추정한다. 이 채널 추정에는 이미 잘 알려진 LS(least-square)와 MMSE(minimum mean-square error)를 사용하였다.

• 대한의용생체공학회:의공학회지
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• 제27권3호
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• pp.89-93
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• 2006

A simple algorithm that can be used to estimate a healthy person's blood pressure using pulse transit time is proposed in this paper. Fifty healthy students participated in the experiment that was conducted in line with the study. The subjects were asked to exercise on several exercise levels using a bicycle ergometer. Their blood pressures during the succeeding rest period were measured. A simple method was proposed to illustrate the relationship between blood pressure and pulse transit time. The systolic blood pressures as well as the heights and weights of the subjects were regarded as the proper parameters, and a second-order regression curve was produced to estimate the subjects' blood pressures. The mean error of estimation was less than 10 mmHg, which was the mean error of manual measurement. Although our estimation model is so simple, it can be used to estimate continuous blood pressure measurement for bicycle ergometer exercise. The electrocardiograms, photoplethysmograms, and blood pressures, however, could not be measured simultaneously As such, their estimation may be slightly different from the results taken from simultaneous measurements.

• 한국농공학회지
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• 제22권3호
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• pp.75-87
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• 1980

Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.

• 전자공학회논문지B
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• 제30B권12호
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• pp.1-11
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• 1993

This paper concentrates on models useful for analyzing the error performance of ML(Maximum Likelihood) estimators of a single unknown signal parameter: that is the error intensity model. We first develop the point process representation for the estimation error and the conditional distribution of the estimator as well as the distribution of error candidate point process. Then the error intensity function is defined as the probability dessity of the estimate and the general form of the error intensity function is derived. We then develop several intensity models depending on the way we choose the candidate error locations. For each case, we compute the explicit form of the intensity function and discuss the trade-off among models as well as the extendability to the case of multiple parameter estimation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.56.1-56
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• 2001

Initial attitude error is one of the large error sources in the navigation errors of SDINS. And it is important to decide the initial attitude of SDINS. The method, like a self-alignment or a transfer alignment method, is required to a precise INS. If we do not have a precise INS, we should get large attitude error. After performing the initial alignment, a vehicle has the initial attitude error. Therefore, it results in navigation error due to the initial attitude error. But, if we use position information during flight, we could estimate and compensate a vehicle attitude error. So, we can maintain a precise attitude in spite of existing the initial attitude error. Using the uplinked position information from a land-based radar system, the new algorithm estimates the attitude of the SDINS during flight ...

• 대한수학회논문집
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• 제33권3호
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• pp.1025-1037
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• 2018

We consider an ill-posed problem for the heat equation $u_{xx}=u_t$ in the quarter plane {x > 0, t > 0}. We propose a new method to compute the heat flux $h(t)=u_x(1,t)$ from the boundary temperature g(t) = u(1, t). The operator $g{\mapsto}h=Hg$ is unbounded in $L^2({\mathbb{R}})$, so we approximate h(t) by $h_{\delta}(t)=u_x(1+{\delta},\;t)$, ${\delta}{\rightarrow}0$. When noise is present, the data is $g_{\epsilon}$ leading to a corresponding heat $h_{{\delta},{\epsilon}}$. We obtain an estimate of the error ${\parallel}h-h_{{\delta},{\epsilon}}{\parallel}$, as well as the error when $h_{{\delta},{\epsilon}}$ is approximated by the trapezoidal rule. With an a priori choice rule ${\delta}={\delta}({\epsilon})$ and ${\tau}={\tau}({\epsilon})$, the step size of the trapezoidal rule, the main theorem gives the error of the heat flux as a function of noise level ${\epsilon}$. Numerical examples show that the proposed method is effective and stable.

• 한국관개배수논문집
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• 제19권1호
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• pp.87-96
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• 2012

Information of local solar radiation is essential for many field, including water resources management, crop yield estimation, crop growth model, solar energy systems and irrigation and drainage design. Unfortunately, solar radiation measurements are not easily available due to the cost and maintenance and calibration requirements of the measuring equipment and station. Therefore, it is important to elaborate methods to estimate the solar radiation based on readily available meteorological data. In this study, two empirical equations are employed to estimate daily solar radiation using Cheongju Regional Meteorological Office data. Two scenarios are considered: (a) sunshine duration data are available for a given location, or (b) only daily cloudiness index records exist. Simple linear regression with daily sunshine duration and cloudiness index as the dependent variable accounted for 91% and 80%, respectively of the variation of solar radiation(H) at 2011. Daily global solar radiation is highly correlated with sunshine duration. In order to indicate the performance of the models, the statistical test methods of the mean bias error(MBE), root mean square error(RMSE) and correlation coefficient(r) are used. Sunshine duration and cloudiness index can be easily and reliably measured and data are widely available.

• 한국통신학회논문지
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• 제37권4A호
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• pp.227-238
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• 2012

본 논문에서는 시분할 반이중 릴레이 통신 시스템을 위한 추정 후 전달 (EF: Estimate and Forward) 릴레이 프로토콜을 제안한다. 기존의 EF 릴레이 프로토콜은 릴레이와 수신국 간 채널 상태가 좋을 때 적용할 수 있는 방식으로 릴레이의 위치가 송신국으로 이동할수록 성능 저하가 크다. 그러나 본 논문에서 제안하는 EF 릴레이 프로토콜은 릴레이에서의 양자화 및 송신국-릴레이 간의 전력 배분 등과 같은 동작 파라미터가 채널 상태 및 변조 차수에 따라 가변적으로 정해지므로 모든 릴레이 위치에 대해 기존의 방식에 비해 낮은 전송 오류율을 보이며 릴레이가 수신국으로부터 멀리 떨어져 있는 경우에도 낮은 전송 오류율을 보인다. 따라서 본 논문에서 제안하는 방식은 릴레이의 위치가 수시로 변하는 이동 릴레이 시스템에 적합하다. 한편, 제안된 방식이 기존의 방식에 비해 모든 릴레이 위치에서 낮은 전송 오류율을 보임을 모의실험을 통해 확인하였다.

• 정보처리학회논문지A
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• 제12A권2호
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• pp.103-108
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• 2005

수학적 모델을 컴퓨터 상에 실현시키는데 있어 보다 효율적인 알고리즘을 구현하고 개발하는 것이 수치해석 연구의 궁극적인 목표이다. 일반적으로 컴퓨터 상에서 구한 계산 결과, 즉 근사 값은 수학적으로 구한 값인 참값과 정확하게 같지 않다 따라서 근사 값이 얼마나 참값에 가까운가를 측정하는 오차평가는 알고리즘의 효율성을 평가하는데 있어 가장 중요한 과제라 할 수 있다. 대부분의 경우 오차평가에 있어 오차의 한계를 이용하지만 주어진 문제의 참값을 모르기 때문에 정확한 오차평가를 할 수 없다. 여기서는 수치등각사상을 구하기 위한 해법중 하나인 Wegmann 방법을 다루는데 저자는 수렴하는 문제의 범위를 넓히기 위해 저주파필터를 적용한 알고리즘을 제안한바 있다. 본 논문에서는 몇 가지 수학적 이론에 근거하여 저주파필터를 적용한 Wegmann해법에서 참값을 모르더라도 오차평가를 할 수 있는 방법을 제안하고 수치실험을 통해 그 유효성을 입증한다.