• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.3
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• pp.355-359
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• 1993

This paper presents a derivation of the optimum convergence constant to yield the most rapid convergence under a desired mean-square error (MSE) for echo canceller using the LMS algorithm. For white input data, the optimum convergence constant is a simple closed-form function of the number of filter taps, the input signal variance, the initial MSE, and the desired MSE. This characteristic makes it easily designed in many practical applications. Computer simulations are also employed to show the correctness and effectiveness of the derived results.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.12
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• pp.1-8
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• 1996

In this paper, we propose a hybrid blind equalizer with TEA and SG (stop & Go) algorithm with switching point a 0 dB of MSE value for improvement of convergence performance, where TEA is used initially to open the eye and then SG algorithm as rapid convergence is employed. The switching point is selected at the point of 0 dB MSE level because of settling the coefficients of blind equalier. As a result of computer simulatons for 8-PAM in the non-minimum phase channel, the proposed algorithm has better convergence speed as 3,500 ~ 4,500 iterations and has better MsE about 3 ~ 6 dB than those of original TEA. Also, computational cost of proposed algorithm is reduced as 5 ~ 16% than that of original TEA. and, the proposed algorithm has better convergence than SG algorithm as 8,500 ~ 17,500 iteratins but, the MSE is similar to original SG.

• Journal of electromagnetic engineering and science
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• v.4 no.1
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• pp.1-7
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• 2004

In this paper the Individual tap - Least Mean Square(IT-LMS) algorithm is applied to the adaptive multipath channel equalization using hybrid-type Genetic Algorithm(GA) for achieving lower minimum Mean Squared Error(MSE). Owing to the global search performance of GA, LMS-type equalizers combined with it have shown preferable performance in both global and local search but those still have unsatisfying minimum MSE performance. In order to lower the minimum MSE we investigated excess MSE of IT-LMS algorithm and applied it to the hybrid GA equalizer. The high convergence rate and lower minimum MSE of the proposed system give us reason to expect that it will perform well in practical multi-path channel equalization systems.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.113-118
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• 2017

This paper propose the NM-MMA (Novel Mixed-MMA) that is possible to improving the convergence speed of current MMA algorithm and reducing the high MSE of SE-MMA algorithm, and its equalization performance were analyzed. The cost function of the NM-MMA configured as the sum of appropriate weights of gradient vector of current MMA and SE-MMA, and then it used for the updating the tap coefficient of equalizer. The computer simulation was performed applying the same environment in the channel, step size and signal to noise ratio, and the same performance index in equalizer output signal constellation, residual isi, MSE, SER was used. As a result of computer simulation, the proposed NM-MMA has fast convergence time than MMA, and less in MSE and SER performance compared to SE-MMA.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.8C
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• pp.795-800
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• 2006

In this paper, the minimum mean square error(MSE) convergence of the RBF equalizer is evaluated and compared with the linear equalizer based on the theoretical minimum MSE. The basic idea of comparing these two equalizers comes from the fact that the relationship between the hidden and output layers in the RBF equalizer is also linear. As extensive studies of this research, various channel models are selected, which include linearly separable channel, slightly distorted channel, and severely distorted channel models. In this work, the theoretical minimum MSE for both RBF and linear equalizers were computed, compared and the sensitivity of minimum MSE due to RBF center spreads was analyzed. It was found that RBF based equalizer always produced lower minimum MSE than linear equalizer, and that the minimum MSE value of RBF equalizer was obtained with the center spread which is relatively higher(approximately 2 to 10 times more) than variance of AWGN. This work provides an analytical framework for the practical training of RBF equalizer system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2A
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• pp.85-90
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• 2009

In this paper, as an alternative to constant modulus algorithm based on MSE, maximization of the probability that equalizer output power is equal to the constant modulus of the transmitted symbols is introduced. The proposed algorithm using the gradient ascent method to the maximum probability criterion has superior convergence and steady-state MSE performance, and the error samples of the proposed algorithm exhibit more concentrated density functions in blind equalization environments. Simulation results indicate that the proposed training has a potential advantage versus MSE training for the constant modulus approach to blind equalization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.10
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• pp.1865-1870
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• 2015

In signal processing, the zero-error probability (ZEP) criterion and related algorithm (MZEP) outperforms MSE-based algorithms and yields superior and stable convergence in impulsive noise environment. In this paper, the analysis of the relationship with MSE criterion proves that ZEP criterion has equivalent optimum solution of MSE criterion. Also this work reveals that the magnitude controlled input of MZEP algorithm plays the role in keeping the optimum solution undisturbed from impulsive noise.

• Journal of Convergence for Information Technology
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• v.11 no.12
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• pp.14-21
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• 2021

In this paper, it is shown how the performance of the monopulse algorithm in the presence of an additive noise can be obtained analytically. In the previous study, analytic performance analysis based on the first-order Taylor series and the second-order Taylor series has been conducted. By adopting the third-order Taylor series, it is shown that the analytic performance based on the third-order Taylor series can be made closer to the performance of the original monopulse algorithm than the analytic performance based on the first-order Taylor series and the second-order Taylor series. The analytic MSE based on the third-order Taylor approximation reduces the analytic MSE error based on the second-order Taylor approximation by 89.5%. It also shows faster results in all cases than the Monte Carlo-based MSE. Through this study, it is possible to explicitly analyze the angle estimation ability of monopulse radar in an environment where noise jamming is applied.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.33-41
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• 2022

In this article, we proposed to predict natural gas (NG) leakage levels through feature selection based on a factor analysis (FA) of the integrating the Korean Meteorological Agency data and natural gas leakage data for considering complex factors. The paper has been divided into three modules. First, we filled missing data based on the linear interpolation method on the integrated data set, and selected essential features using FA with OrdinalEncoder (OE)-based normalization. The dataset is labeled by K-means clustering. The final module uses four algorithms, K-nearest neighbors (KNN), decision tree (DT), random forest (RF), Naive Bayes (NB), to predict gas leakage levels. The proposed method is evaluated by the accuracy, area under the ROC curve (AUC), and mean standard error (MSE). The test results indicate that the OrdinalEncoder-Factor analysis (OE-F)-based classification method has improved successfully. Moreover, OE-F-based KNN (OE-F-KNN) showed the best performance by giving 95.20% accuracy, an AUC of 96.13%, and an MSE of 0.031.

• Journal of the Korea Computer Industry Society
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• v.6 no.3
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• pp.447-456
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• 2005

This paper describes iterative restoration method of restoring blurred images using the LOG compansion function and Conjugate Gradient method. Conventional restoration methods results satisfy the requirement performance for restoring blurred images. but iteration number and convergence velocity increase. This paper proposed an opmtimised iteration restoration method for the images degraded by blurring effect, using the LOG compansion function and Conjugate Gradient method. Here, the LOG compansion function used to improve local properties of the image being restored, made the visual character and convergence velocity of the restored image improved. Throught the simulation results, the author showed that proposed algorithm produced superior performance results by conventional methods.