• Journal of the Institute of Electronics Engineers of Korea TC
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• v.38 no.3
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• pp.9-18
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• 2001

In this paper, we present the joint symbol detection and channel estimation for an orthogonal frequency division multiplexing (OFDM) system in fading channels. The proposed methods are based on decision-directed channel estimation (DDCE) method and their symbol detection is achieved by using Viterbi algorithm. This Viterbi decision-directed channel estimation (VDDCE) method tracks time-varying channels and detects a maximum likelihood symbol sequence. Recursive Viterbi decision-directed channel estimation (RVDDCE) method based on VDDCE method is proposed to shorten the detecting depth. In this method, channel estimate and Viterbi processing are recursively performed every interval of training symbol. Also, average chann'el estimation (ACE) technique to reduce the effect of additive white Gaussian noise (AWGN) is applied VDDCE method and RVDDCE method. These proposed methods arc demonstrated by computer simulation.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.3
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• pp.188-195
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• 2004

This paper presents neural load torque observer that is used to deadbeat load torque observer and gain compensation by parameter estimator As a result, the response of the PMSM(permanent magnet synchronous motor) follows that nominal plant. The load torque compensation method is composed of a neural deadbeat observer To reduce the noise effect, the post-filter implemented by MA(moving average) process, is adopted. The parameter compensator with RLSM (recursive least square method) parameter estimator is adopted to increase the performance of the load torque observer and main controller The parameter estimator is combined with a high performance neural load torque observer to resolve the problems. The neural network is trained in on-line phases and it is composed by a feed forward recall and error back-propagation training. During the normal operation, the input-output response is sampled and the weighting value is trained multi-times by error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque. As a result, the proposed control system has a robust and precise system against the load torque and the Parameter variation. A stability and usefulness are verified by computer simulation and experiment.

• The Korean Journal of Applied Statistics
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• v.24 no.1
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• pp.103-114
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• 2011

Current series for testing stock market cointegrations tend to be restricted to analyzing the relations between stock market prices and may not be able to understand the whole picture of the variations in the stock market system. The nature of the variations in the stock prices, between the countries that experienced economic crisis and those did not, are different for a certain period of time, and accordingly excluding the potentially important variables in the stock market system causes statistical bias. This study considers domestic foreign exchange markets and financial markets in testing for the cointegrating relations of the stock prices in Korea and major investing countries. The results demonstrate the possibility of specification errors unless those markets are included in the statistical modeling process.

• Journal of Advanced Navigation Technology
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• v.7 no.2
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• pp.217-226
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• 2003

Recently Lim has proposed a linear, recursive, unbiased minimum variance filter for a maneuvering target based on the maneuver dynamics modeled as a jump process of Poisson-type. In the proposed filter it was assumed that the state transition parameters of the jump used for target maneuver modeling are a priori known to the filter. However, in most cases they are not known in practice. In this paper, we consider the influence of system (target) modeling error on the performance of the proposed tracking filter arising from the maneuver tracking. For qualitative analysis Monte-Carlo simulations are carried out against employing the maneuver model with different state transition parameters from the actual values.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1352-1355
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• 1996

The control of diamond turning is usually achieved through a laser-interferometer feedback of slide position. If the tool post is rigid and the material removal process is relatively static, then such a non-collocated position feedback control scheme may surface. However, as the accuracy requirement gets tighter and desired surface contours become more complex, the need for a direct tool-tip sensing becomes inevitable. The physical constraints of the machining process prohibit any reasonable implementation of a tool-tip motion measurement. It is proposed that the measured force normal to the face of the workpiece can be filtered through an appropriate admittance transfer function to result in the estimated depth of cut. This can be compared to the desired depth of cut to generate the adjustment control action in addition to position feedback control. In this work, the design methodology on the admittance model-based control with a conventional controller is presented. The recursive least-squares algorithm with forgetting factor is proposed to identify the parameters and update the cutting process in real time. The normal cutting forces are measured to identify the cutting dynamics in the real diamond turning process using the precision dynamometer. Based on the parameter estimation of cutting dynamics and the admittance model-based nanodynamic control scheme, simulation results are shown.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.2
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• pp.188-194
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• 2014

Recently, indoor localization systems based on wireless sensor networks have received a great deal of attention because they help achieve high accuracy in position determination by using various algorithms. In order to minimize the error in the estimated azimuth that can occur owing to sensor drift and recursive calculation in these algorithms, we propose a novel relative azimuth estimation algorithm. The advantages of the proposed technique in an indoor environment are that an improved weight average filter is used to effectively reduce impulse noise from the raw data acquired from nodes with inherent errors and a rotational displacement algorithm is applied to obtain a precise relative azimuth without using additional sensors, which can be affected by electromagnetic noise. Results from simulations show that the proposed filter reduces the impulse noise, and the acquired estimation error does not accumulate with time by using proposed algorithm.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.12
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• pp.109-117
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• 2015

In this paper, we proposed error-reducing method to source or measure a current or voltage for LED in the I-V characteristic analysis system using a digital signal processor (DSP). this method has the advantage of reducing a non-linear circuit error and random error. random error can be reduced using recursive averaging technique and non-linear circuit error can be reduced using 2rd polynomial regression calibration parameters fitting with measured sample data. it corrects measured error of IR, VR, VF1, VF2, VF3 of LED using calibration parameters. experimental results show that can be performed with about 0.017~0.043% accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.1
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• pp.29-37
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• 1992

In this paper, a new and easy analytical method to get the Fourier transforms of a popular type of truncated raised cosine function and its powers (n=1, 2, :1‥‥ : positive integers) Is proposed. This new. method is based on the concept of the ( 1+D)_type partial response system, and the procedure is more compact than the conventional method using differentiations. Especially, the results are obtained as a sum of three functions which are easily manageable for each power And they are recursively related to their powers. Therefore, they can be excellently applied to the computer-aided numerical solutions.

• Journal of Power Electronics
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• v.8 no.4
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• pp.354-362
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• 2008

This paper presents neural load torque compensation method which is composed of a deadbeat load torque observer and gains compensation by a parameter estimator. As a result, the response of the PMSM (permanent magnet synchronous motor) obtains better precision position control. To reduce the noise effect, the post-filter is implemented by a MA (moving average) process. The parameter compensator with an RLSM (recursive least square method) parameter estimator is adopted to increase the performance of the load torque observer and main controller. The parameter estimator is combined with a high performance neural load torque observer to resolve problems. The neural network is trained in online phases and it is composed by a feed forward recall and error back-propagation training. During normal operation, the input-output response is sampled and the weighting value is trained multi-times by the error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque. As a result, the proposed control system has a robust and precise system against load torque and parameter variation. Stability and usefulness are verified by computer simulation and experiment.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.154-157
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• 1990

This paper describes a new method of calculating expected energy generation and loss of load probability (L.O.L.P) for electric power system operation and expansion planning. The method represents an equivalent load duration curve (E.L.D.C) as a mixture of cumulants approximation (M.O.C.A), which is the general case of mixture of normals approximation (M.O.N.A). By regarding a load distribution as many normal distributions-rather than one normal distribution-and representing each of them in terms of Gram-Charller expansion, we could improve the accuracy of results. We developed an algorithm which automatically determines the number of distribution and demarcation points. In modelling of a supply system, we made subsets of generators according to the number of generator outage: since the calculation of each subset's moment needs to be processed rapidly, we futher developed specific recursive formulae. The method is applied to the test systems and the results are compared with those of cumulant, M.O.N.A and Booth-Baleriaux method. It is verified that the M.O.C.A method is faster and more accurate than any other methods.