• The Journal of the Acoustical Society of Korea
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• v.36 no.2
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• pp.100-107
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• 2017

The focused MVDR (Minimum Variance Distortionless Response) can be applied for source localization in near field. However, if the number of sensors are increased, it requires a large amount of calculation to obtain the inverse of the covariance matrix. In this paper we propose a focused MVDR method using that beam space is formed from output of far field beamformer at the subarray. The performances of the proposed method was evaluated by simulation. As a result of simulation, the proposed method has the higher spatial resolution performance then the conventional delay-and-sum beamformer.

• Industrial Engineering and Management Systems
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• v.7 no.1
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• pp.44-50
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• 2008

Focusing on the exponential smoothing method equivalent to (1, 1) order ARMA model equation, a new method of estimating smoothing constant using exponential smoothing method is proposed. This study goes beyond the usual method of arbitrarily selecting a smoothing constant. First, an estimation of the ARMA model parameter was made and then, the smoothing constants. The empirical example shows that the theoretical solution satisfies minimum variance of forecasting error. The new method was also applied to the stock market price of electrical machinery industry (6 major companies in Japan) and forecasting was accomplished. Comparing the results of the two methods, the new method appears to be better than the ARIMA model. The result of the new method is apparently good in 4 company data and is nearly the same in 2 company data. The example provided shows that the new method is much simpler to handle than ARIMA model. Therefore, the proposed method would be better in these general cases. The effectiveness of this method should be examined in various cases.

• Journal of KSNVE
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• v.10 no.4
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• pp.642-647
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• 2000

Conventional cepstrum has been widely used to detect echo and fault signals embedded in noise. One of the problems of finding impulse signals using the conventional cepstrum in that it is normally very sensitive to signal to noise ratio (SNR). This paper proposes a signal processing method to detect impulse signal in noisy environment. Because the proposed method minimizes the variance of signal power at a cepstrum domain, it is suggested to be called as minimum variance cepstrum (MV cepstrum). Computer simulations have been performed to understand the characteristics of the MV cepstrum. Both mathematical approach and computer simulations confirmed that the MV cepstrum is a useful technique to detect impulse in noisy environment.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.1
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• pp.14-20
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• 1996

This paper presents a self tuning method of a velocity type PID controller for minimum or non-minimum phase systems with time delays. The velocity type PID control structure is determined in the process of minimizing the variance of the auxilliary output, and self tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing a design parameter. This method is simple and effective compared with other existing methods[1,2]. Numerical examples are included to illustrate the procedure and to show the performance of the control system.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.3
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• pp.388-394
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• 2003

Hydraulic system is difficult to obtain a suitable performance due to the nonlinearity load pressure change and system parameter variation. The requirement of control a1gorithm has been complex in order to satisfy the performance. The adaptive control is a control method which is suggested to achieve the control object under the plant characteristics change. In spite of the case that plant characteristics and the degree of variation are difficult to grasp. the adaptive control could keep the characteristics of closed-loop system generally. In this study. a method of combined generalized minimum variance adaptive control (GMVAC) and output error feedback is proposed, in order to solve the problem of non-minimum phase of plant and the vibration and overshoot in initial response. The control performance according to the variation of characteristics of plant is evaluated by changing the supply pressure. The experimental results show the effectiveness of the proposed scheme.

• Industrial Engineering and Management Systems
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• v.8 no.4
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• pp.257-263
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• 2009

Focusing on the idea that the equation of exponential smoothing method (ESM) is equivalent to (1, 1) order ARMA model equation, new method of estimation of smoothing constant in exponential smoothing method is proposed before by us which satisfies minimum variance of forecasting error. Theoretical solution was derived in a simple way. Mere application of ESM does not make good forecasting accuracy for the time series which has non-linear trend and/or trend by month. A new method to cope with this issue is required. In this paper, combining the trend removal method with this method, we aim to improve forecasting accuracy. An approach to this method is executed in the following method. Trend removal by a linear function is applied to the original shipping data of consumer goods. The combination of linear and non-linear function is also introduced in trend removal. For the comparison, monthly trend is removed after that. Theoretical solution of smoothing constant of ESM is calculated for both of the monthly trend removing data and the non monthly trend removing data. Then forecasting is executed on these data. The new method shows that it is useful especially for the time series that has stable characteristics and has rather strong seasonal trend and also the case that has non-linear trend. The effectiveness of this method should be examined in various cases.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.8-13
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• 2023

We propose a method for removing interference and noise to estimate target information. In wireless channels, information signals are subject to interference and noise, making it is difficult to accurately estimate the desired signal. To estimate the desired information signal, it is essential to remove the noise and interference from the received signal, extracting only the desired signal. If the received signal noise and interference are not removed, the estimated information signal will have a large error in distance and direction, and the exact location of the target cannot be estimated. This study aims to accurately estimate the desired target in space. The objective is to achieve more presice target estimation than existing methods and enhance target resolution.An estimation method is proposed to improve the accuracy of target estimation. The proposed target estimation method obtains optimal weights using linear constraints and the minimum variance method. Through simulation, the performance of the proposed method and the existing method is analyzed. The proposed method successfully estimated all four targets, while the existing method only estimated two targets. The results show that the proposed method has better resolutiopn and superior estimation capability than the existing method.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.215-218
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• 1998

This paper proposes a blind multi-user detector using Code-Constrained Minimum Variance (CCMV) method which directly detects the DS-CDMA signals in a multipath fading channel without estimating the channels. This algorithm reduces the complexity of computation by making a small size data matrix with the order of the channel length. Advantageously it requires to know the spreading code and the time delay of only the desired user.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.3
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• pp.1-5
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• 2011

In this thesis, we have developed novel geometrical analysis method for the double constraints linear constraint minimum variance (LCMV) beamforming algorithm. The proposed analysis method was matched well with the computer simulation result.

• Journal of the Korean Statistical Society
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• v.32 no.4
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• pp.411-423
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• 2003

In this paper we develop a method for calculating a probability that a particular generalized variance is the smallest of all the K multivariate normal generalized variances. The method gives a way of comparing K multivariate populations in terms of their dispersion or spread, because the generalized variance is a scalar measure of the overall multivariate scatter. Fully parametric frequentist approach for the probability is intractable and thus a Bayesian method is pursued using a variant of weighted Monte Carlo (WMC) sampling based approach. Necessary theory involved in the method and computation is provided.