• Journal of Korean Society for Quality Management
• /
• v.25 no.1
• /
• pp.69-79
• /
• 1997

We consider the semiparametric linear errors-in-variables model: yi=(${\alpha}+{\beta}ui+{\varepsilon}i$, xi=ui＋${\varepsilon}i$ i=1, …, n where (xi, yi) stands for an observation vector, (ui) denotes a set of incidental nuisance parameters, (${\alpha}$ , ${\beta}$) is a vector of regression parameters and (${\varepsilon}i$, ${\delta}i$) are mutually uncorrelated measurement errors with zero mean and finite variances but otherwise unknown distributions. On the basis of a simple small-sample low-noise a, pp.oximation, we propose a new method of comparing the mean squared errors(MSE) of the various competing estimators of the true regression parameters ((${\alpha}$ , ${\beta}$). Then we show that a class of estimators including the classical least squares estimator and the maximum likelihood estimator are consistent and first-order efficient within the class of all regular consistent estimators irrespective of type of measurement errors.

• Journal of Korean Society for Quality Management
• /
• v.22 no.2
• /
• pp.89-97
• /
• 1994

We consider the linear calibration model: $y_1={\alpha}+{\beta}x_i+{\sigma}{\varepsilon}_i$, i = 1, ${\cdots}$, n, $y={\alpha}+{\beta}x+{\sigma}{\varepsilon}$ where ($y_1$, ${\cdots}$, $y_n$, y) stands for an observation vector, {$x_i$} fixed design vector, (${\alpha}$, ${\beta}$) vector of regression parameters, x unknown true value of interest and {${\varepsilon}_i$}, ${\varepsilon}$ are mutually uncorrelated measurement errors with zero mean and unit variance but otherwise unknown distributions. On the basis of simple small-sample low-noise approximation, we introduce a new method of comparing the mean squared errors of the various competing estimators of the true value x for finite sample size n. Then we show that a class of estimators including the classical and the inverse estimators are consistent and first-order efficient within the class of all regular consistent estimators irrespective of type of measurement errors.

• IEIE Transactions on Smart Processing and Computing
• /
• v.3 no.2
• /
• pp.83-87
• /
• 2014

This paper introduces a refined opportunistic interference alignment (OIA) technique that uses minimum mean square error (MMSE) detection at the receivers in multiple-input multiple-output multi-cell uplink networks. In the OIA scheme under consideration, each user performs the optimal transmit beamforming and power control to minimize the level of interference generated to the other-cell base stations, as in the conventional energy-efficient OIA. The result showed that owing to the enhanced receiver structure, the OIA scheme shows much higher sum-rates than those of the conventional OIA with zero-forcing detection for all signal-to-noise ratio regions.

• Proceedings of the KIEE Conference
• /
• 1988.07a
• /
• pp.709-712
• /
• 1988

Ultrasonic Doppler Diagnostic System utilizes the Doppler effect for measurement of blood velocity. The sign of the Doppler frequency shift represents blood flow direction. CW(Continuous-Wave) Doppler System uses quadrature detection and phase rotation method to produce simultaneous independent audio and velocity signals for forward and reverse blood flow direction in the time-domain, had been fabricated. But time-domain analyzing such as audio evaluation and zero- crossing detection for instantaneous and mean frequnecy measurement do not provide both an accurate and quantitative result. Therefore, it is necessary to adopt frequency-domain technique to improve system performance. In this paper, we describe a unit which is composed of CW Doppler System and real-time spectrum analyzer (installed TMS 32010 DSP Chip). This unit shows time-dependent spectrum variation and mean velocity of Blood signal.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 1997.10a
• /
• pp.223-230
• /
• 1997

A method of stochastic dynamic analysis of suspension bridge subjected to random wind loads has been developed in this paper. Example analyses are carried out by mode superposition method(MSM), mode acceleration method(MAM) and advanced mode acceleration method(AMAM) in frequency domain for the Nam-Hae Bridge. In this study the statistical characterics of random wind loads we assumed to be Gaussian stationary zero mean processes. The considered structural response quanties are displacements, shear forces and bending moments. The mean extreme responses are approximately calculated by three times of standard deviations. The followings are the conclusions from this study. 1. Numerical results which obtained by three methods of computer program developed in this paper agree reasonably well when the numbers of modes increase. 2. AMAM is simple, accurate, economic and reliable method compared with the MSM and the MAM.

• ETRI Journal
• /
• v.16 no.2
• /
• pp.15-25
• /
• 1994

In this paper we present a new formula which can predict the exact detection probability of a generalized order statistics (GOS) constant false alarm rate (DFAR) detector for a partially correlated Rayleigh target model (0 < $ \rho$< 1) in a closed form, where $\rho$ is the correlation coefficient between returned pulses. By simply substituting a set of specific coefficient into the derived formula, one can obtain the detection probability of any kind of CFAR detector. Detectors may include the order statistics CFAR detector, the censored mean level detector, and the trimmed mean CFAR detector, but are not necessarily restricted to them. The numerical result for the first order Markov correlation model as applied to some of the detectors shows that as $\rho$ increases from zero to one, higher signal-to-noise ratio is required to achieve the same detection probability.

• Bulletin of the Korean Chemical Society
• /
• v.30 no.11
• /
• pp.2717-2722
• /
• 2009

The use of the classification and regression tree (CART) methodology was studied in a quantitative structure-activity relationship (QSAR) context on a data set consisting of the binding affinities of 39 imidazobenzodiazepines for the α1 benzodiazepine receptor. The 3-D structures of these compounds were optimized using HyperChem software with semiempirical AM1 optimization method. After optimization a set of 1481 zero-to three-dimentional descriptors was calculated for each molecule in the data set. The response (dependent variable) in the tree model consisted of the binding affinities of drugs. Three descriptors (two topological and one 3D-Morse descriptors) were applied in the final tree structure to describe the binding affinities. The mean relative error percent for the data set is 3.20%, compared with a previous model with mean relative error percent of 6.63%. To evaluate the predictive power of CART cross validation method was also performed.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.16 no.12
• /
• pp.1274-1285
• /
• 1991

This paper presents a statistical convergence analysis of the normalized least mean square(NLMS)algorithm that employs a single-pole lowpass filter, In this algorithm the lowpass filter is used to adjust its output towards the estimated value of the input signal power recursively. The estimated input signal power so obtained at each time is then used to normalize the convergence parameter. Under the assumption that the primary and reference inputs to the adaptive filter are zero mean wide sense stationary, and Gaussian random processes, and further making use of the independence assumption. we derive expressions that characterize the mean and maen squared behavior of the filter coefficients as well as the mean squared estimation error. Conditions for the mean and mean squared convergence are explored. Comparisons are also made between the performance of the NLMS algorithm and that of the popular least mean square(LMS) algorithm Finally, experimental results that show very good agreement between the analytical and emprincal results are presented.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.11C
• /
• pp.641-648
• /
• 2011

Frequency domain equalization is the most promising technology that has relatively low complexity in multipath channel. A frame of single carrier system with frequency domain equalization (SC-FDE) has cyclic prefix to mitigate effect of delay spread. After synchronization and equalization procedure on the SC-FDE system, common phase offset (CPO) that can introduce performance degradation caused by phase mismatch between transmitter and receiver oscillators is remained. In this paper, common phase offset tracking in frequency domain is proposed. To track CPO, constant amplitude zero autocorrelation code sequence as training sequence is adopted. By using numerical results, performance of mean square error is evaluated. The results show that MSE of CPO has similar performance compare to the time-domain estimation and there is no need of domain conversion.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.11 no.3
• /
• pp.17-22
• /
• 2011

In this paper, we analyze co-channel interference cancellation performance to be generated in multi-hop military communication system. First, remove interference using zero-forcing (ZF) and minimum mean square error (MMSE) scheme as interference cancellation methods, and then obtain additional diversity gain and improve interference cancellation performance by applying successive interference cancellation (SIC). We consider Rayleigh fading channel and system performance is analyzed as respect of bit error probability. From simulation results, we confirm MMSE improves significantly BER performance than ZF in multi-hop wireless network environment. It is also confirmed ZF and MMSE schemes applying SIC algorithm have better performance comparing to the existing schemes. Therefore, MMSE-SIC method can provide more reliable signal transmission in the multi-hop military communication system.