• Journal of Satellite, Information and Communications
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• v.7 no.1
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• pp.53-58
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• 2012

In this paper, we evaluate and analyze representative estimation methods for the sparse channel. In order to evaluate error performance of matching pursuit(MP) and minimum mean square error(MMSE) algorithm, lower bound of MMSE is determined by Cramer-Rao bound and compared with upper bound of MP. Based on analysis of those bounds, mean square error of MP which is effective in the estimation of sparse channel can be larger than that of MMSE according to the number of estimated tap and signal-to-noise ratio. Simulation results show that the performances of both algorithm are reversed on the sparse channel with Rayleigh fading according to signal-to-noise ratio.

• The Journal of the Acoustical Society of Korea
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• v.14 no.1E
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• pp.56-64
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• 1995

The least mean fourth (LMF) adaptive algorithm is a stochastic gradient method that minimizes the error in the mean fourth sense. Despite its potential advantages, the algorithm is much less popular than the conventional least mean square (LMS) algorithm in practice. This seems partly because the analysis of the LMF algorithm is much more difficult than that of the LMS algorithm, and thus not much still has been known about the algorithm. In this paper, we explore the statistical convergence behavior of the LMF algorithm when the input to the adaptive filter is zero-mean, wide-sense stationary, and Gaussian. Under a system idenrification mode, a set of nonlinear evolution equations that characterizes the mean and mean-squared behavior of the algorithm is derived. A condition for the conbergence is then found, and it turns out that the conbergence of the LMF algorithm strongly depends on the choice of initial conditions. Performances of the LMF algorithm are compared with those of the LMS algorithm. It is observed that the mean convergence of the LMF algorithm is much faster than that of the LMS algorithm when the two algorithms are designed to achieve the same steady-state mean-squared estimation error.

• The Journal of the Acoustical Society of Korea
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• v.22 no.3
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• pp.224-232
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• 2003

In this paper, efficient deployment method of sensors and target positioning performance with respect to measurement error are dealt with. Active sonar can be categorized into Monostatic, Bistatic, Multistatic sonar, and characteristics of respective sonar are different. Assuming that each sensor can receive range and angular information, we compare the performance of Monostatic, Bistatic, and Multistatic systems. And we suggest Weighted least square (WLS) which gives the weight to former case, LS. In particular. adopting suggested method we investigate the target positioning performance according to number of sensor, distance from transmitter to receiver, and propose efficient arrangement rule for Multistatic sonar configurations. According to the experimental results, RMSE of Multistatic sonar is found to be superior to Monostatic and Bistatic by 35.98%. 37.45% respectively, and WLS is superior to LS approximately by 7.4% in average. Furthermore, as the difference of respective sensor's variance is large, it is observed that the improvement ratio of target positioning performance is increased.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.10
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• pp.2303-2309
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• 1997

This paper presents a convergence analysis of the stocastic gradient adaptive algorithm based on the least mean absolute third (LMAT) error criteriohn. Under the assumption that the signals involved are zero-mean, wide-sense sateionaryand gaussian, a set of nonlinear difference equations that characterizes the mean and mean-squared behavior of the algorithm is derived. Computer simulation resutls show fairly good agreements between the theoetical and empirical behaviors of the algorithm.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.675-684
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• 1998

This paper presents the empirical formulas for determining the design-width for medium rivers in the Han river basin. The design flood, the watershed ares, and the channel slope of 216 medium rivers in the Han river basin are collected. the design width formulas are then determined by 1) the least squares (LS) method, 2)the least median squares (LMS) method, and 3) the reweighted least squares method based on the LMS (RLS). The six types of formulas are considered to determine the acceptable type for medium streams in the Han river basin. The root mean squared errors (RMSE), the absolute mean (AME) errors, and the mean errors (ME) are computed to test the formulas derived by three regression methods. It si found that the equation related stream width to the watershed area and the channel slope is acceptable for determining the design width for medium streams in the Han river basin. It is expected that the equations proposed by this study be used an index for determining the design-width for medium streams in the Han river basin.

• The Journal of the Acoustical Society of Korea
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• v.38 no.3
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• pp.283-289
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• 2019

RLS (Recursive-least-squares) algorithm is known to have good convergence and excellent error level after convergence. However, there is a disadvantage that numerical instability is included in the algorithm due to inverse matrix calculation. In this paper, we propose an algorithm with no matrix inversion to avoid the instability aforementioned. The proposed algorithm still keeps the same convergence performance. In the proposed algorithm, we adopt an averaged gradient-based step size as a self-adjusted step size. In addition, a variable forgetting factor is introduced to provide superior performance for time-varying channel estimation. Through simulations, we compare performance with conventional RLS and show its equivalency. It also shows the merit of the variable forgetting factor in time-varying channels.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.10
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• pp.2310-2316
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• 1997

This paper presents a comparative performance analysis of the stochastic gradient adaptive algorithm based on the least mean absolute third (LMAT) error criterion with other widely-used competing adaptive algorithms. Under the assumption that the signals involved are zero-mean, wide-sense stationary and Gaussian, approximate expressions that characterize the steady-state mean-squared estimation error of the algorithm is dervied. The validity of our derivation is then confirement by computer simulations. The convergence speed is compared under the condition that the LMAT and other competing algorithms converge to the same value for the mean-squared estimation error in the stead-state, and superior convergence property of the LMAT algorithm is observed. In particular, it is shown that the LMAT algorithm converges faster than other algorithms even through the eignevalue spread ratio of the input signal and measurement noise power change.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.3
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• pp.809-823
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• 1991

본 연구에서는 Wiener 필터링 이론에 의하여 소음원의 입력신호에 대한 최적 한 예측을 할 수 있는 최적예측기(optimal predictor)로써 부가적인 음을 발생시키고 입력신호 및 출력신호 간의 차인 오차를 최소화시키도록 하는 적응신호처리방법에 대 해 설명하고 이러한 적응 신호처리 방법을 이용한 능동 소음 제어 방법을 제시하였다. 이와 아울러 제어계의 환경 변화에 따른 파라메타의 변화에 적응적으로 응답이 가능해 야 하는 적응 소음 제어계에서, 음향궤환과 함께 필히 고려해야하는 부가적인 전달함 수-모델과 스피커를 포함하는 보조경로 및 오차미이크로폰을 포함하는 오차경로의 전 달함수의 영향을 고려한 능동소음제어에 대해 연구하였다.

• Journal of Korean Society of Transportation
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• v.18 no.4
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• pp.117-126
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• 2000

Conventional methods for collecting origin-destination trips have been mainly relied on the surveys of home or roadside interview. However, the methods tend to be costly, labor intensive and time disruptive to the trip makers, thus the methods are not considered suitable for Planning applications such as routing guidance, arterial management and information Provision, as the parts of deployments in Intelligent Transport Systems Motivated by the problems, more economic ways to estimate origin-destination trip tables have been studied since the late 1970s. Some of them, which have been estimating O-D table from link traffic counts are generally Entropy maximizing, Maximum likelihood, Generalized least squares(GLS), and Bayesian inference estimation etc. In the Paper, with user equilibrium constraint we formulate GLS problem for estimating O-D trips and develop a solution a1gorithm by using Genetic Algorithm, which has been known as a g1oba1 searching technique. For the purpose of evaluating the method, we apply it to Seoul inner ringroad and compare it with gradient method proposed by Spiess(1990). From the resu1ts we fond that the method developed in the Paper is superior to other.

• International Journal of Highway Engineering
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• v.10 no.1
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• pp.145-154
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• 2008

The purpose of this study is to evaluate the quality of on-line departure time-based link travel time estimates. For this, accuracy (i.e. estimation error) and timeliness (i.e. degree of time lag) are proposed as MOE of the quality of on-line link travel time estimates. Then the relationship between quality of link travel time estimates and link length and level of congestion is analyzed. It was found that there is trade-off between the accuracy and timeliness of link travel time estimates. The estimation error was modeled to consist of two components: one is systematic error and the other is mean square error which reflects level of congestion. further, time lag was again segmented into three parts for the analysis purpose. There are minimum one, congestion-related one, and update interval-related one. From the real-world data using AVI system, it was revealed that regardless of the link length and level of congestion, 10 minutes of time lag occurs in general.