• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.12
• /
• pp.1183-1187
• /
• 2011

In this paper, an optimal FIR (Finite-Impulse-Response) filter is proposed for discrete time-varying state-space models. The proposed filter estimates the current state using measured output samples on the recent time horizon so that the variance of the estimation error is minimized. It is designed to be linear, unbiased, with an FIR structure, and is independent of any state information. Due to its FIR structure, the proposed filter is believed to be robust for modeling uncertainty or numerical errors than other IIR filters, such as the Kalman filter. For a general system with system and measurement noise, the proposed filter is derived without any artificial assumptions such as the nonsingular assumption of the system matrix A and any infinite covariance of the initial state. A numerical example show that the proposed FIR filter has better performance than the Kalman filter based on the IIR (Infinite- Impulse-Response) structure when modeling uncertainties exist.

• Speech Sciences
• /
• v.11 no.2
• /
• pp.237-245
• /
• 2004

In general, Gaussian mixture model(GMM) is used to estimate the speaker model for speaker identification. The parameter estimates of the GMM are obtained by using the expectation-maximization (EM) algorithm for the maximum likelihood(ML) estimation. However, if the number of mixtures isn't defined well in the GMM, those parameters are obtained inappropriately. The problem to find the number of components is significant to estimate the optimal parameter in mixture model. In this paper, to estimate the optimal number of mixtures, we propose the method that starts from the sufficient mixtures, after, the number is reduced by investigating the mutual information between mixtures for GMM. In result, we can estimate the optimal number of mixtures. The effectiveness of the proposed method is shown by the experiment using artificial data. Also, we performed the speaker identification applying the proposed method comparing with other approaches.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2004.05b
• /
• pp.318-322
• /
• 2004

This study was conducted to derive the regional design rainfall by the regional frequency analysis based on the regionalization of the precipitation. For the estimation of the regional design rain(all, classification of the climatologically and geographically homogeneous regions should be preceded preferentially The optimal regionalization of the precipitation data were classified by the above mentioned conditions for all over the regions except Jeju and Ulleung islands in Korea. Relative root mean square error(RRMSE), relative bias(RBIAS) and relative reduction(RR) in RRMSE for the design rainfall were computed and compared between the regional and at-site frequency analysis. Consequently, optimal design rainfalls following the classified regions and consecutive durations were derived by the regional frequency analysis using GEV distribution which was identified to be more optimal one than the other applied distributions.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2002.12a
• /
• pp.399-405
• /
• 2002

Now days, it is based on GIS and GPS, it can search for the shortest path and estimation of arrival time by using the internet and cell phone to driver. But, even though good car navigation system does not create which is the shortest path when there average vehicle speed is 10 -20 Km. Therefore In order to reduce vehicle waiting time and average vehicle speed, we suggest optimal green time algorithm using fuzzy adaptive control , where there are different traffic intersection length and lane. In this paper, it will be able to forecast the optimal traffic Information, estimation of destination arrival time, under construction road, and dangerous road using internet.

• Communications for Statistical Applications and Methods
• /
• v.31 no.3
• /
• pp.337-347
• /
• 2024

Kernel density estimation is a prevalent technique employed for nonparametric density estimation, enabling direct estimation from the data itself. This estimation involves two crucial elements: selection of the kernel function and the determination of the appropriate bandwidth. The selection of the bandwidth plays an important role in kernel density estimation, which has been developed over the past decade. A range of methods is available for selecting the bandwidth, including the plug-in bandwidth. In this article, the proposed plug-in bandwidth is introduced, which leverages shifted Chebyshev series-based approximation to determine the optimal bandwidth. Through a simulation study, the performance of the suggested bandwidth is analyzed to reveal its favorable performance across a wide range of distributions and sample sizes compared to alternative bandwidths. The proposed bandwidth is also applied for kernel density estimation on real dataset. The outcomes obtained from the proposed bandwidth indicate a favorable selection. Hence, this article serves as motivation to explore additional plug-in bandwidths that rely on function approximations utilizing alternative series expansions.

• Journal of the Korean Data and Information Science Society
• /
• v.13 no.2
• /
• pp.39-44
• /
• 2002

We compare MISE of the MLE, UMVUE, invariantly optimal estimator and Jacknife estimator for the reliability function of the Weibull distribution when the sample size is small.

• 전기의세계
• /
• v.34 no.2
• /
• pp.94-98
• /
• 1985

Autocorrelation에 관계되는 Fourier변환의 기본적인 성질을 이용하여 speckle잡음제거가 power spectrum estimation 문제와 같이 해석될 수 있다는 것을 보였고 spectral estimation 방법으로서 최대 entrppy방법을 사용하여 딴 방법들과 비교하여 볼때 좋은 결과를 얻었다. 앞으로 2차원 test object까지의 확장, 이 알고리즘의 각 파라메타들에 대한 sensitivity, optimal한 Hanning window크기 판단 기준으로서 normalized mean squared error(NMSE)를 사용하였다.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.3 no.2 s.5
• /
• pp.129-140
• /
• 2004

In this paper, we conduct the research about optimal aggregation interval of travel time data on interrupted traffic flow and verify the reliability of AVI collected data by using car plate matching method in RTMS for systematic collection and analysis of link travel time data on interrupted traffic flow rural arterial. We perform Kolmosorov-Smirnov test on AVT collected sample data and on entire population data, and conclude that the sample data does not represent pure random sampling and hence includes sample collection error. We suggest that additional review is necessary to investigate the effectiveness of AVI collected sample data as link representative data. We also develop statistical model by applying two estimation techniques namely point estimation and interval estimation for calculating optimal aggregation interval. We have implemented our model and determine that point estimate is preferable over interval estimate for exactly selecting and deciding optimal aggregation interval. Our final conclusion is that 5-minute aggregation interval is optimal to estimate travel time in RTMS, as is currently being used our investigation is based on AVI data collected from Yang-ji to Yong-in $42^{nd}$ National road.

• Korean Journal of Remote Sensing
• /
• v.34 no.2_1
• /
• pp.191-201
• /
• 2018

In this present study, we, for the first time, retrieved total column of ozone ($O_3$) and tropospheric ozone vertical profile using the Optimal Estimation (OE) method based on the MAX-DOAS measurement at the Yonsei University in Seoul, Korea. The optical density fitting is carried out using the OE method to calculate ozone columns. The optical density between the MAX-DOAS data obtained by dividing the measured intensities for each viewing elevated angle by those at the zenith angle. The retrieved total columns of the ozone are 375.4 and 412.6 DU in the morning (08:13) and afternoon (17:55) on 23 May, 2017, respectively. In addition, under 10 km altitude, the $O_3$ vertical profile was retrieved with about 5% of retrieval uncertainty. However, above 10 km altitude, the $O_3$ vertical profile retrieval uncertainty was increased (>10%). The spectral fitting errors are 16.8% and 19.1% in the morning and afternoon, respectively. The method suggested in this present study can be useful to measure the total ozone column using the ground-based hyper-spectral UV sensors.

• Korean Journal of School Psychology
• /
• v.17 no.3
• /
• pp.263-286
• /
• 2020

The purpose of this study was to explore how overly positive self-estimations in peer relationships relate to subjective well-being and to the occurrence of interpersonal behaviors supporting basic psychological needs among elementary school students. This study tested the optimal margin hypothesis of positive illusion by examining the curvilinear relationship between these variables. The sample consisted of 346 fifth and sixth grade students. The self-criterion residual method was used to derive self-estimation bias scores by regressing the real peer relations index (i.e., In-degree) on their perceived peer relationship qualities. The results showed that girls more strongly overestimated the quality of their peer relationships than boys. Self-estimation biases had a positive curvilinear relationship with negative affects and a negative curvilinear relationship with relatedness needs supporting interpersonal behaviors. These results supported the existence of the optimal margin of positive illusion because overestimations of the quality of peer relationships were associated with lower levels of negative affects and relatedness needs-supporting interpersonal behaviors, though these benefits flattened out and no further benefit was observed after an optimal level of overestimation. However, self-estimation bias was linearly associated with positive affect, autonomy needs-supporting interpersonal behaviors, and competence needs-supporting interpersonal behaviors. These results indicated that optimal margin hypothesis was not supported for all outcome variables.