• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.29-35
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• 2006

The third generation mobile communications system requiring the reliable multimedia data transmission has provided with the reliable voice, data and video services over the variable propagation environment. However the broadband wireless multiple access technologies cause Inter Symbol Interference(ISI) or Multiple Access Interference(MAI) to degrade the performance of CDMA(Code Division Multiple Access) system. Constant Modulus Algorithm which is frequently used as the adaptive blind equalizers to remove the interfering signal has ill-convergence phenomenon without proper initialization. In this paper, new blind equalization method based on conventional CMA is proposed to improve the channel efficiency, and through computer simulation this is tested over the time varying fading environment of mobile communication system. consequently, new blind equalization method into concatenated Kalman filter with CMA is verified better than conventional CMA through adopting minimum mean square errors and eye-pattern obtained from algorithm are compared.

• Journal of Internet Computing and Services
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• v.10 no.1
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• pp.11-17
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• 2009

Blind equalization techniques have been used in multipoint communication on which the research on the internet has focused. In this paper, a criterion of minimizing Euclidian Distance between two PDFs for adaptive blind equalizers has been presented. In order for ED expressed with Parzen PDFs to be minimized, we propose to use a set of randomly generated desired symbols at the receiver so that the PDF of the generated symbols matches that of the transmitted symbols. From the simulation results, the proposed method has shown superior error performance even in severe channel environments in which CMA has shown severe performance degradation. This indicates that the proposed algorithm can be considered relatively insensitive to ESR variations compared to CMA. As a field of ITL, ED minimization using Parzen PDFs has shown possibilities of being successfully applied to blind equalization.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.85-91
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• 2014

This paper relates with the VSDA (Variable stepsize Square contour Decision directed Algorithm) adaptive equalization algorithm that is used for the minimization of the intersymbol interference due to the distortion which occurs in the time dispersive channel for the transmission of 16-QAM signal.. In the conventional SCA, it is possible to compensates the amplitude and phase in the received signal that are mixed with the intersymbol interference by the constellatin dependent constant by using the 2nd order statistics of the transmitted signal. But in the VSDA, it is possible to the increasing the equalization performance by adding the concept of distance adjusted approach for constellation matching and the cost function of decision directed. We compare the performance of VSDA and SCA algorithm by the computer simulation. For this, the equalizer output signal constellation, residual isi, maximum distortion and MSE were used in the performace index. As a result of computer simulation, the VSDA algorithm has better than the SCA in convergence speed, but it gives nearly same equalization performance in other index.

• The Journal of the Acoustical Society of Korea
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• v.31 no.1
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• pp.1-10
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• 2012

The linear and decision-feedback equalization can mitigate time-varying intersymbol interference (ISI) caused by time-varying multipath propagation for underwater acoustic channels. The perfect elimination of interference components, however, is difficult using the linear equalization and the decision feedback equalizer has an error propagation problem. To overcome these shortcomings, this paper proposes an equalizer mode selection method using training sequences. The proposed method selects an equalization mode corresponding to the signal-to-noise ratio (SNR). If the SNR is low, the proposed system operates the linear equalizer for preventing the error propagation and if the SNR is high, the decision feedback equalizer for eliminating the residual ISI. Therefore, the proposed method can improve the error performance compared to the conventional equalizers. The computer simulation shows the proposed method improves the bit error performance using practical underwater channels responses acquired from the sea experiment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.27-34
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• 2013

This paper deals with the performance anlysis of CCA adaptive equalization algorithm, that is used for reduction of intersymbol interference at the receiving side which occurs in the time dispersive communication channel. Basically, this algorithm is borned for the solving phase unrecovery problem in the CMA equalizer, and the comines the concept of DDA (Decision Directed Algorithm) and RCA (Reduce Constellation Algorithm). The DDA has a stable convergence characteristics in unilevel signal, but not in the number of levels in multilevel signal such as QAM, so it has unstable problem. The RCA does not provide reliable initial convergence. And even after convergence, the equalization noise due to the steady state misadjustment exhibited by it is very high as compared to DDA. For the solving the abovemensioned point, the CCA adaptive eualization alogorithm has borned. In order to performance analysis of CCA algorithm, the recovered signal constellation that is the output of the equalizer, the convergence characteristic by the residual isi and MD (maximum distortion), the SER characteristic are used by computer simulation and it was compared with the DDA, RCA respectively. As a result of simulation, the DDA has superior performance than other algoithm, but it has a convergence unguarantee and unstability in the multilevel signal. In order to solving this problem, the CCA has more good performance than RCA in every performance index.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.7-13
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• 2012

The performance of blind equalization algorithm ISCA was compared with MSCA that is used for the minimization of the inter symbol interference which occurs in the time dispersive communication channel for digital transmission. Because of the non-linearities of a magnitude and phase transfer characteristics of a communication channel, the transmitting signal will be received that band limited and time dispersived. Therefore the distortion was compensated by using the self adaptive equalizer at the receiving side, then passing through the detector for the decision of "1" or "0". At this time the Constellation Dependent Constant is played an important role in the adaptive equalizer used on the receiver. In order to calculation of this constant, the ISCA and MSCA was used the second order statistics. The ISCA and MSCA which are possible to compensation of mensioned transfer function simulataneously, are improved the performance of original SCA algorithm and then was compared the performance by computer simulation. For this, the recovered constellation, residual isi and MSE was used, and a result of performance comparison, the ISCA algorithm has better than the MSCA in every performance index. But on the steady state of equalizer, the variation of performance due to the CME terms in the MSCA equalization algorithm was less than the ISCA, so MSCA has better stability.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.12
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• pp.2397-2408
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• 1994

In this paper, a structure for a nonlinear adaptive equalizer is discussed to reduce nonlinearity in digital high-density recording systems. We propose a nonlinear adaptive decision feedback equalizer which can reduce the nonlinear intersymbol interference increasing with high-density recording systems, and compare its performance with the RAM-DFE which is designed to remove nonlinear intersymbol interference existing in postcursor part. By observing the output SNR of each equalizer applied to recording channels with three different densities. we confirm that the nonlinear adaptive decision feedback equalizer performs the best in the general case where nonlinear intersymbol interference exists in both precursor and postcursor parts.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.703-715
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• 2017

Mammogram images are sensitive in nature and even a minor change in the environment affects the quality of the images. Due to the lack of expert radiologists, it is difficult to interpret the mammogram images. In this paper an algorithm is proposed for a computer-aided diagnosis system, which is based on the wavelet based adaptive sigmoid function. The cascade feed-forward back propagation technique has been used for training and testing purposes. Due to the poor contrast in digital mammogram images it is difficult to process the images directly. Thus, the images were first processed using the wavelet based adaptive sigmoid function and then the suspicious regions were selected to extract the features. A combination of texture features and gray-level co-occurrence matrix features were extracted and used for training and testing purposes. The system was trained with 150 images, while a total 100 mammogram images were used for testing. A classification accuracy of more than 95% was obtained with our proposed method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.474-476
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• 2009

In the radio communication, such as echo cancellation and channel equalization, adaptive filtering is very practical. Its convergence behavior that is used for updating the weights depends on the correlation of the input signal and length of adaptive filter. Highly correlated input and long length of adaptive filter deteriorate the convergence behavior. To solve this problem, recently, subband affine projection algorithm which pre-whiten the correlation of the input and update the weights in subband structure has been presented. This paper presents convergence analysis method of multiple constrained subband affine projection algorithm.