• The Journal of the Acoustical Society of Korea
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• v.28 no.8
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• pp.815-821
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• 2009

Information processing in variable and noisy environments is usually accomplished by means of adaptive filters. Among various adaptive algorithms, Least Mean Square (LMS) has become the most popular for its robustness, good tracking capabilities and simplicity, both in terms of computational load and easiness of implementation. In practical application of the LMS algorithm, the most important key parameter is the Step Size. As is well known, if the Step Size is large, the convergence rate of the algorithm will be rapid, but the steady state mean square error (MSE) will increase. On the other hand, if the Step Size is small, the steady state MSE will be small, but the convergence rate will be slow. Many researches have been proposed to alleviate this drawback by using a variable Step Size. In this paper, a new variable Step Size LMS(VSSLMS) called Categorized VSSLMS (CVSSLMS) is proposed. CVSSLMS updates the Step Size by categorizing the current status of the gradient, hence significantly improves the convergence rate. The performance of the proposed algorithm was verified from the view point of convergence rate, Excessive Mean Square Error(EMSE), and complexity through experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.2
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• pp.178-183
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• 1993

This paper presents a new optimal range of the step size to converge LMS adaptive algorithm considering quantization error of equalizer coefficient and excess MSE. And the simulation of transversal equalizer shows the propriety of it.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.105-110
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• 2018

This paper compare the adaptive equalization performance of NM-MMA (Novel Mixed-MMA) algorithm which using the mixed const function by scaling factor values. The mixed cost function of NM-MMA composed of the appropriate weighted addition of gradient vector in the MMA and SE-MMA cost function, and updating the tap coefficient based on these function, it is possible to improve the convergence speed and MSE value of current algorithm. The computer simulation was performed in the same channel, step size, SNR environment by changing the scaling factor, and its performance were compared appling the equalizer output constellation, residual isi, MD, MSE, SER. As a result of computer simulation, the residual values of performance index were reduced in case of the scaling factor of MMA cost function was greater than the scaling factor of SE-MMA. and the convergence speed was improved in case of the scaling factor of SE-MMA was greater than the MMA.

• 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.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.27-32
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• 2021

This paper evaluates the equalization performance of FC-MMA adaptive equalization algorithm by the fixed step size that is used for the minimization of the intersymbol interference which occurs in the time dispersive communication channel. The FC-MMA has a fast convergence speed in order to adapts the new environment more rapidly in case of the time varying charateristics and the abnormal situation like as outage of the communication channel. But the algorithms operates in adative method, convegence speed is depend on fixed step size for adaptation. For this situation, its performance was evaluated by changing the step size value, the residual isi and maximum distortion and MSE performance index which means the convergence characteristics are widely adapted in the adaptive equalizer, SER were applied. As a result of computer simulation, the large step size can improves the convergence speed for reaching the steady state, but has a poor performance compared to small step size in residual values after steady state. The research result shows that the FC-MMA algorithm is applied the large step size for rapidly reaching the steady state in initial time, then adjust the small step size after reaching the steady state for reducing the residual values for equalization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.995-1000
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• 2016

The maximum cross-correntropy (MCC) algorithm with a set of random symbols keeps its optimum weights undisturbed from impulsive noise unlike MSE-based algorithms and its main factor has been known to be the input magnitude controller (IMC) that adjusts the input intensity according to error power. In this paper, a normalization of the step size of the MCC algorithm by the power of IMC output is proposed. The IMC output power is tracked recursively through a single-pole low-pass filter. In the simulation under impulsive noise with two different multipath channels, the steady state MSE and convergence speed of the proposed algorithm is found to be enhanced by about 1 dB and 500 samples, respectively, compared to the conventional MCC algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.51-56
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• 2019

This paper related with the performance comparison of CCA and RMMA blind adaptive equalization in order to reduce the intersymbol interference which is occurred in channel when transmitting the 16-QAM signal, high spectrum efficiencies of nonconstant modulus characteristic. The CCA possible to improve the misadustment and initial convergence by compacting the every signal constellation of 16 by using the sliced symbol of the decision device output, namely statistical symbol, but incresing the computational cost. The RMMA possible to minimize the fast convergence speed and misadjustment and channel tracking capability without increasing the computational cost by obtain the error signal after transform to 4 constant modulus signal based on the region of signal constellation located. In this paper, these algorithm were implemented in the same channel, and the blind adaptive equalization performance were compared using the equalizer output signal constellation, residual isi, MSE, SER. As a result of simulation, the RMMA has better performance in output signal constellation, residual isi and MSE compared to the CCA, but has slow convergence speed about 1.3 times. And the SER performance presenting the robustness to the noise signal, the CCA has more beeter in less SNR, but the RMMA has better in greater than 6dB in SNR.

• Journal of Korea Multimedia Society
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• v.3 no.4
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• pp.365-371
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• 2000

To restore image degraded by out-of-focus blur and additive noise, an iterative restoration is used. Acceleration parameter is usually applied equally to all over the image without considering the local characteristics of degraded images. As a result, the conventional methods are not effective in restoring severely degraded edge region and shows slow convergence rate. To solve this problem we propose an adaptive iterative restoration according to local degradation, in which the acceleration parameter has low value in flat region that is less degraded and high value in edge region that is more degraded. Through experiments, we verified that the proposed method showed better results with fast convergence rate, showed Visually better image in edge region and lower MSE than the conventional methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.7
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• pp.1364-1373
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• 1994

In this thesis, an algorithm for fast convergence to the steady state and for achieving an improved MSE in blind adaptive equalizers is proposed. The conventional radius-directed algorithm can be transformed into an algorithm that provides effective blind convergence in the aspect of the MSE as the convergence speed. This can be achieved through altering the stop and go algorithm. The performance of the new algorithm is analyzed and compared with the two conventional algorithms, such as the CMA and the stop and go algorithm. The experimental results show the superiority of the new algorithm.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.5
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• pp.549-554
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• 2014

In the paper, we propose a new Signed LMS(Least Mean Square) algorithm for ICS(Interference Cancellation System). The proposed Signed LMS algorithm improved performances by adjusting step size values. At the convergence of 1000 iteration state, the MSE(Mean Square Error) performance of the proposed Signed LMS algorithm with step size of 0.067 is about 3 ~ 18 dB better than the conventional LMS, CMA algorithm. And the proposed Signed LMS algorithm requires 500 ~ 4000 less iterations than the and LMS and CMA algorithms at MSE of -25dB.