• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.27-32
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• 2020

This paper compare the adaptive equalization performance according to the values of adaptive step variation speed for adapting in VS-CCA (Variable Stepsize-Compact Constellation Algorithm) based on nonlinear function function of error signal. The VS-CCA algorithm compacts the 16-QAM nonconstant modulus signal into the 4 groups of 4-QAM constant modulus signal constellation in quadature plane, then the error signal is generated using the constant modulus of transmitted signal statistics. The adaptive equalizer coefficient were updated in order to achieve the minimum cost function by varying step based on the nonlinear function of error signal. In this time, the instantaneous adaptive step is determined according to the value of step variation speed of nonlinear function and the different equalization performance were obtained according to the step variation speed value. The equalizer internal index and external index which represents the robustness of external noise were used for the performance comparison index. As a result of computer simulation, it was confirmed that the value of variation speed less than 1.0 give more superior in every performance index compared to the greater than 1.0 in steady state.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.4
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• pp.433-442
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• 2010

In this paper, self-calibration algorithm based on covariance matrix is proposed for compensating amplitude/phase mismatch in multi-baseline interferometer direction finding system. The proposed method is a solution to nonlinear constrained minimization problem which dramatically calibrate mismatch error using space sector concept with cost function as defined in this paper. This method, however, has a drawback that requires an estimated initial angle to determine the proper space sector. It is well known that this type of drawback is common in nonlinear optimization problem. Superior calibration capabilities achieved with this approach are illustrated by simulation experiments in comparison with interferometer algorithm for a varitiety of amplitude/phase mismatch error. Furthermore, this approach has been found to provide an exceptional calibration capabilities even in case amplitude and phase mismatch are more than 30 dB and over $5^{\circ}$, respectively, with sector spacing of less than $50^{\circ}$.

• Journal of IKEEE
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• v.13 no.1
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• pp.1-10
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• 2009

Recently, some frequency domain CMA (Constant Modulus Algorithm) have been introduced in an effort to reduce computational complexities [1,2]. In [1], a fast algorithm that minimizing cost function designed for block input signal is employed, while in [2], a novel cost function that minimizing sample by sample input is used. Although, the two fast algorithm save computational complexities as compared to CMA, the convergence behaviors of the two fast algorithm show different results with repsect to CMA. Thus, in this paper, some analytical results on the error surface of the fast frequency domain CMA are introduced. From the analytical results, we show that the more recent algorithm [2] outperforms the previous algorithm [1]. Simulation results reveals that the recent algorithm [2] shows 50% enhanced convergence with respect to the old fast algorithm [1]. Also, we show that the recent fast algorithm [2] has comparable convergence performance with respect to conventional CMA algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.4
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• pp.137-143
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• 2010

This paper deals with the performance comparison of self adaptive equalizer by the weighting factor of MCMA cost function for the compensate the amplitude and phase distortion which occurs in the communication channel. The MCMA is improves the cost function of present CMA at the output of equalizer for the minimize of error function in the amplitude and phase, the value of weighting factor is used at this time. When the comparison of equalizer performance, we classified to initial state and steady state, then it represents the convergence time and convergence speed and steady state operation of equalizer to the predetermined level, it is determined by the weighting factor. We confirm to the different result to this 2 state by weighting factor values using computer simulation. By using the result of this paper, if we appropriately choose the weighting factor values in the environment of communication channel, it is expected that the high quality digital transmission is possible.

• The Journal of the Acoustical Society of Korea
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• v.14 no.1
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• pp.22-30
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• 1995

In this Paper we study the convergence behavior of the least mean fourth (LMF) algorithm where the error raised to the power of four is minimized for a multiple sinusoidal input and Gaussian measurement noise. Here we newly obtain the convergence equation for the sum of the mean of the squared weight errors, which indicates that the transient behavior can differ depending on the relative sizes of the Gaussian noise and the convergence constant. It should be noted that no similar results can be expected from the previous analysis by Walach and Widrow.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.7
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• pp.3-8
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• 2016

We propose a modified form of the decision-directed least mean square (DD LMS) algorithm that is widely used in the optimization of self-adaptive equalizers, and show the modified version greatly improves the initial convergence properties of the conventional algorithm. Existing DD LMS regards the difference between a equalizer output and a quantization value for it as an error, and achieves an optimization of the equalizer based on minimizing the mean squared error cost function for the equalizer coefficients. This error generating method is useful for binary signal or a single-level signals, however, in the case of multi-level signals, it is not effective in the initialization of the equalizer. The modified DD LMS solves this problem by modifying the error generation. We verified the usefulness and performance of the modified DD LMS through experiments with multi-level signals under distortions due to intersymbol interference and additive noise.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.142-152
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• 2016

GPS is not able to be used for indoor positioning and currently most of techniques emerging to overcome the limit of GPS utilize private wireless networks. However, these methods require high costs for installation and maintenance, and they are inappropriate to be used in the place where precise positioning is needed as in indoor parking lots. This paper proposes a vehicular indoor positioning method based on QR-code recognition. The method gets an absolute coordinate through QR-code scanning, and obtain the location (an relative coordinate) of a black-box camera using the tilt and roll angle correction through affine transformation, scale transformation, and trigonometric function. Using these information of an absolute coordinate and an relative one, the precise position of a car is estimated. As a result, average error of 13.79cm is achieved and it corresponds to just 27.6% error rate in contrast to 50cm error of the recent technique based on wireless networks.

• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.105-113
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• 2002

As the number of pedestrian accident increases, the reconstruction of an accident becomes important to find the source of the fault. Generally, accidents are reconstructed by the intuition of experts or primitive physics. A reconstruction method is proposed using sophisticated optimization technology. At first, a dynamic simulation model is established for the accident environment. Occupant analysis for automobile crashworthiness is employed. The situation before an accident is identified by optimization. The impact velocity and the position of the pedestrian are utilized as design variables. The design variables are found by minimizing the difference between the simulation and the real accident. The optimization process is performed by linking an occupant analysis program MADYMO to an optimization program VisualDOC. Since the involved analysis is dynamics and highly nonlinear, response surface method is selected for the optimization process. Problems are solved for various situations.

• The Korean Journal of Applied Statistics
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• v.33 no.1
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• pp.11-23
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• 2020

Sampling design should provide statistics to meet a given accuracy while saving cost and time. However, a large number of non-responses are occurring due to the deterioration of survey circumstances, which significantly reduces the accuracy of the survey results. Non-responses occur for a variety of reasons. Chung and Shin (2017, 2019) and Min and Shin (2018) found that the accuracy of estimation is improved by removing the bias caused by non-response when the response rate is an exponential or linear function of variable of interests. For that case they assumed that the error of the super population model follows normal distribution. In this study, we proposed a non-response bias adjusted estimator in the case where the error of a super population model follows the gamma distribution or the log-normal distribution in a business survey. We confirmed the superiority of the proposed estimator through simulation studies.

• Journal of Internet Computing and Services
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• v.21 no.2
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• pp.49-55
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• 2020

Information theoretic learning (ITL) methods based on random symbols (RS) use a set of random symbols generated according to a target distribution and are designed nonparametrically to minimize the cost function of the Euclidian distance between the target distribution and the input distribution. One drawback of the learning method is that it can not utilize the input power statistics by employing a constant stepsize for updating the algorithm. In this paper, it is revealed that firstly, information potential input (IPI) plays a role of input in the cost function-derivative related with information potential output (IPO) and secondly, input itself does in the derivative related with information potential error (IPE). Based on these observations, it is proposed to normalize the step-size with the statistically varying power of the two different inputs, IPI and input itself. The proposed algorithm in an communication environment of impulsive noise and multipath fading shows that the performance of mean squared error (MSE) is lower by 4dB, and convergence speed is 2 times faster than the conventional methods without step-size normalization.