• The Korean Journal of Applied Statistics
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• v.7 no.2
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• pp.239-248
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• 1994

The Yule-Walker estimator and the approximate conditional least squares estimator of the parameter of the EARMA(1, 1) model are obtained. These two estimators are compared by simulation study. It is shown that the approximate conditional least squares estimator is better in the sense of the mean square error than the Yul-Walker estimator.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.419-424
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• 1992

A robust nonlinear predictive control strategy using a disturbance estimator is presented. The disturbance estimator is comprised of two parts: one is the disturbance model parameter adaptation and the other is future disturbance prediction. RLSM(recurrsive least square method) with a forgetting factor is used to de the uncertain distance model parameters and for the future disturbance prediction, future process outputs and inputs projected by the process model are used. The simulation results for chemical reactors indicate that a substantial improvement in nonlinear predictive control performance is possible using the disturbance estimator.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.33-41
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• 1994

A single channel adaptive noise canceling (ANC) technique with a recursive time delay estimator (RTDE) is presented for removing effects of additive noise on the speech signal. While the conventional method makes a reference signal for the adaptive filter using the pitch estimated on a frame basis from the input speech, the proposed method makes the reference signal using the delay estimated recursively on a sample-by-sample basis. As the RTDEs, the recursion formulae of autocorrelation function (ACF) and average magnitude difference function (AMDF) are derived. The normalized least mean square (NLMS) and recursive least square (RLS) algorithms are applied for adaptation of filter coefficients. Experimental results with noisy speech demonstrate that the proposed method improves the perceived speech quality as well as the signal-to-noise ratio and cepstral distance when compared with the conventional method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.2
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• pp.111-116
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• 2009

In this paper, we propose a phase offset estimation algorithm which is based on turbo coded digital broadcasting system. The phase estimator is an estimator outside turbo code decoder using LMS (Least Mean Square) algorithm to estimate the phase of next state. While the conventional LMS algorithm with a fixed step size is easy implemented, it has weak points that are difficult the channel estimation and tracking in the multipath environment. To resolve this problem, we propose new phase offset estimation method with a variable step size LMS (VS-LMS). Additionally, we propose a scheme which consists of a conventional LMS. The performance is verified by computer simulation according to a fixed phase offset and a increased phase offset, the proposed algorithm improve the bit error rate performance than the conventional algorithm.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.1 no.3
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• pp.69-76
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• 2008

This paper concerns Fuzzy Radial Basis Function Neural Network (FRBFNN) and automatic rule generation of extraction of the FRBFNN by means of mountain clustering. In the proposed network, the membership functions of the premise part of fuzzy rules do not assume any explicit functional forms such as Gaussian, ellipsoidal, triangular, etc., so its resulting fitness values (degree of membership) directly rely on the computation of the relevant distance between data points. Also, we consider high-order polynomial as the consequent part of fuzzy rules which represent input-output characteristic of sup-space. The number of clusters and the centers of clusters are automatically generated by using mountain clustering method based on the density of data. The centers of cluster which are obtained by using mountain clustering are used to determine a degree of membership and weighted least square estimator (WLSE) is adopted to estimate the coefficients of the consequent polynomial of fuzzy rules. The effectiveness of the proposed model have been investigated and analyzed in detail for the representative nonlinear function.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.48 no.3
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• pp.139-143
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• 1999

This paper is on realization of the speed-sensorless vector control of an induction motor using the RLS(Recursive Least Square) algorithm. The speed estimator is including the RLS algorithm and a rotor flux observer. The RLS algorithm has speed and rotor time constant as parameter vectors and rotor flux observer is designed to have robustness to stator resistance variation and through the IP(Integral and Proportional) speed controller stable performance is obtained for estimating rotor speed. Finally the total algorithm are realized in induction motor drive system and its effectiveness is verified.

• The Journal of the Acoustical Society of Korea
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• v.25 no.3E
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• pp.123-130
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• 2006

The adaptive echo canceller (AEC) has become an important component in speech communication systems, including mobile station. In these applications, the acoustic echo path has a long impulse response. We propose a running-average least mean square (RALMS) algorithm with a detection method for acoustic echo cancellation. Using colored input models, the result clearly shows that the RALMS detection algorithm has a convergence performance superior to the least mean square (LMS) detection algorithm alone. The computational complexity of the new RALMS algorithm is only slightly greater than that of the standard LMS detection algorithm but confers a major improvement in stability.

• Proceedings of the IEEK Conference
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• 2000.06a
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• pp.45-48
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• 2000

The use of multi-level modulation scheme in the wireless LAN(Local Area Networks) system requires an accurate channel estimation. In this paper, we present sequential least squares(LS) channel estimation scheme based on decision-directed channel tracking scheme. The proposed scheme improves the performance of the conventional LS estimator for wireless LAN. In addition, its structure is suitable for the high-rate wireless LAN. Simulation results show that the proposed scheme achieves about IdB Packet Error Rate(PER) gain compared to the LS scheme in a frequency selective channel.

• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.745-754
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• 2006

It has been shown that LAD estimates are more efficient than LS estimates when the error distribution is double exponential in AR(1) model. In order to explore the performance of LAD estimates one can use bootstrap approaches. In this paper we consider the efficiencies of bootstrap methods when we apply LAD estimates with highly variable data. Monte Carlo simulation results are given for comparing generalized bootstrap, stationary bootstrap and threshold bootstrap methods.

• Communications for Statistical Applications and Methods
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• v.25 no.6
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• pp.577-590
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• 2018

Employing the covariance adjustment technique, we show that in the system of two seemingly unrelated multivariate regressions the estimator of regression coefficients can be expressed as a matrix power series, and conclude that the matrix series only has a unique simpler form. In the case that the covariance matrix of the system is unknown, we define a two-stage estimator for the regression coefficients which is shown to be unique and unbiased. Numerical simulations are also presented to illustrate its superiority over the ordinary least square estimator. Also, as an example we apply our results to the seemingly unrelated growth curve models.