• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.10
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• pp.2275-2284
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• 2015

In this paper, the Walsh coded orthogonal training signals for 4 × 4 multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems are designed and the channel estimation equations are derived as a closed form, taking account of the inter training signal interference problems caused by the multi-path delayed signals. The performances of the proposed channel estimation method are analyzed and compared with the conventional methods[9,14] by using computer simulation. The simulation results show that the proposed methods has better performances, compared with the conventional methods[9,14]. As a result, the proposed method can be used for MIMO-OFDM systems with null sub-carriers.

• Advances in aircraft and spacecraft science
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• v.7 no.6
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• pp.495-516
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• 2020

Nonlinear state estimation is a desirable and required technique for many situations in engineering (e.g., aircraft/spacecraft tracking, space situational awareness, collision warning, radar tracking, etc.). Due to high standards on performance in these applications, in the last few decades, there was an increasing demand for methods that are able to provide more accurate results. However, because of the mathematical complexity introduced by the nonlinearities of the models, the nonlinear state estimation uses techniques that, in practice, are not so well-established which, leads to sub-optimal results. It is important to take into account that each method will have advantages and limitations when facing specific environments. The main objective of this paper is to provide a comprehensive overview and interpretation of the most well-known methods for nonlinear state estimation with Gaussian priors. In particular, the Kalman filtering methods: EKF (Extended Kalman Filter), UKF (Unscented Kalman Filter), CKF (Cubature Kalman Filter) and EnKF (Ensemble Kalman Filter) with an aerospace perspective.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.12A
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• pp.1296-1302
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• 2007

In this paper, we propose joint estimation methods of carrier offset and channel estimation for MB-OFDM system with low complexity. The proposed methods estimate the channel by using low-rank LMMSE channel estimation which reduces the system complexity by applying the optimal number of rank to evaluate the frequency offset and additionally using the simple algorithm using the auto-correlation property of the estimated channel. We simulate the proposed algorithms under the IEEE 802.15 TG3a UWB channel model.

• Bulletin of the Korean Chemical Society
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• v.24 no.3
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• pp.279-284
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• 2003

The One Pass Method (OPM) previously presented for the identification of single input single output systems is used to estimate the parameters of a Decentralized Control System (DCS). The OPM is a linear and therefore a simple estimation method. All of the calculations are performed in one pass, and no initial parameter guess, iteration, or powerful search methods are required. These features are of interest especially when the parameters of multi input-output model are estimated. The benefits of the OPM are revealed by comparing its results against those of two recently published methods based on pulse testing. The comparison is performed using two databases from the literature. These databases include single and multi input-output process transfer functions and relevant disturbances. The closed loop responses of these processes are roughly captured by the previous methods, whereas the OPM gives much more accurate results. If the parameters of a DCS are estimated, the OPM yields the same results in multi or single structure implementation. This is a novel feature, which indicates that the OPM is a convenient and practice method for the parameter estimation of multivariable DCSs.

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.1
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• pp.45-51
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• 2005

This paper presents a comparison of rotor position estimation of a switched reluctance motor(SRM) with built-in search coils by three methods. The search coil EMFs are not generated in the SRM with built-in search coils at standstill. So an initial rotor position estimation method is needed. In this paper squared euclidean distance, fuzzy logic and neural network methods we proposed for the estimation of initial rotor position. The simulated results of the three methods are compared. The simulated result of the squared euclidean distance method, which has the best performance, is supported by the experimental result.

• The Korean Journal of Applied Statistics
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• v.5 no.2
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• pp.255-268
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• 1992

We propose an iterated interpolation approach for the estimation fo time series parameters in the presence of outliers. The proposed approach iterates the parameter estimation stage and the outlier detection stage until no further outliers are detected. For the detection of outliers, interpolation diagnostic is applied, where the atypical observations by the one-step-ahead predictor instead of downweighting is also proposed. The performance of the proposed estimation methods is compared with other robust estimation methods by simulation study. It is observed that the iterated interpolation approach performs reasonably well is general, especially for single AO case and large $\phi$ in absolute values.

• Bulletin of the Korean Space Science Society
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• 2011.04a
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• pp.25.4-25.4
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• 2011

Various estimation methods based on Kalman filter have been applied to the real-time satellite orbit determination. The most popular method is the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF). The EKF is easy to implement and to use on orbit determination problem. However, the linearization process of the EKF can cause unstable solutions if the problem has the inaccurate reference orbit, sparse or insufficient observations. In this case, the UKF can be a good alternative because it does not contain linearization process. However, because both methods are based on Gaussian assumption, performance of estimation can become worse when the distribution of state parameters and process/measurement noise are non-Gaussian. In nonlinear/non-Gaussian problems the particle filter which is based on sequential Monte Carlo methods can guarantee more exact estimation results. This study develops and tests the particle filter for satellite orbit determination. The particle filter can be more effective methods for satellite orbit determination in nonlinear/non-Gaussian environment.

• Journal of Environmental Science International
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• v.20 no.3
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• pp.321-327
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• 2011

Bootstrap methods is the computer-based resampling method that estimates the standard errors and confidence intervals of summary statistics using the plug-in principle for assessing the accuracy or uncertainty of statistical estimates, and the BCa method among the Bootstrap methods is known much superior to other Bootstrap methods in respect of the standards of statistical validation. Therefore this study suggests the method of the representation and treatment of uncertainty in flood risk assessment and water resources planning from the construction and application of rainfall frequency analysis model considersing the uncertainty based on the nonparametric BCa method among the Bootstrap methods for the assessement of the estimation of probability rainfall and the effect of uncertainty considering the uncertainty of the parameter estimation of probability in the rainfall frequency analysis that is the most fundamental in flood risk assessement and water resources planning.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.185-193
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• 2022

There have been various studies in Korea to develop a %IMF(Intramuscular Fat Percentage) estimation method suitable for Hanwoo. Recently, a %IMF estimation method using a convolutional neural network (CNN), a kind of deep learning method among artificial intelligence methods, has been studied. In this study, we performed a performance comparison when various preprocessing methods were applied to the %IMF estimation of ultrasound images using CNN as mentioned above. The preprocessing methods used in this study are normalization, histogram equalization, edge enhancement, and a method combining normalization and edge enhancement. When estimating the %IMF of Hanwoo by the conventional method that did not apply preprocessing in the experiment, the accuracy was 98.2%. The other hand, we found that the accuracy improved to 99.5% when using preprocessing with histogram equalization alone or combined regularization and edge enhancement.

• Journal of Oral Medicine and Pain
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• v.14 no.1
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• pp.43-55
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• 1989

The need of age estimation for identification was increased by complexity of society, and the tooth was used widely for age estimation because of less individual deviation than the other organ. The age estimation using the tooth had several methods. Recently, the one using the racemization of aminoacid in the tooth was admitted more accurate than the other methods, especially in old age. But, this study was not tried in our country, and I would report the result of experiment about age estimation using racemization of dentine. I selected 40-Whole dentine sample from extracted teeth, those were reserved in natural dried condition for 2 weeks~ 1year and calculated the estimation of age from the ratio of D-aminoacid and L-aminoacid (D/L ratio) using gaschromatography and the results were below. 1. The aminoacids showed apparent K/L ratio in dentine were aspartic acid, serine. 2. The aspartic acid showed the highest racemic rate and its rate was 0.0012$\pm$0.0003/yr. 3. The relation between the actual age and K/L ratio was very positive correlation(r+0.954) in the estimation of age using aspartic acid. 4. The deviation between the estimated age using D/L ratio of aspartic acid and actual age was $\pm$3.32.