• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.4
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• pp.427-432
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• 2010

To reduce the outage probability and to increase the transmission capacity, the importance of repeaters in cellular systems is increasing. But a RF(Radio Frequency) repeater has a problem that the output of the transmit antenna is partially feedback to the receive antenna, which is feedback interference. In this paper, we proposed adaptive Sign-Sign LMS(Least Mean Square) algorithm using correlations for the performance enhancement of RF repeater. The weight vector is updated by using sign of input signal and error signal to the least squared error of the conventional algorithms. When compared with the conventional method, the proposed canceller achieves the maximum 10 dB performance gain in terms of the MSE(Mean Square Error).

• Journal of information and communication convergence engineering
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• v.8 no.2
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• pp.159-162
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• 2010

This paper presents a new Kurtosis driven Variable Step-Size Normalized Least Mean Square (KVSSN-LMS) algorithm to prevent repeater from oscillation due to feedback signal of radio frequency (RF) repeater. To get better Mean Square Error (MSE) performance, step-size is adjusted using the kurtosis. The proposed algorithm shows the better performance of steady state MSE. The proposed algorithm shows a better ERLE performance than that of KVSS-LMS, VSS-NLMS, NLMS algorithms.

• Journal of IKEEE
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• v.17 no.2
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• pp.145-150
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• 2013

In the paper, we propose a new CSS(Complex Signed-Signed) CMA(Constant Modulus Algorithm) algorithm for ICS(Interference Cancellation System). When the repeater get the feedback signal, the CSS CMA algorithm is proposed at the ICS repeater using DSP(Digital Signal Processing) for the removal of interfering signals from the feedback paths. The proposed CSS CMA algorithm improved performances and hardware complexity by adjusting step size values. the steady state MSE(Mean Square Error) performance of the proposed CSS CMA algorithm with step size of 0.00043 is about 4dB better than the conventional CMA algorithm. And the proposed Complex Signed Signed CMA algorithm requires 1950 ~ 2150 less iterations than the LMS(Least Mean Square) and Signed LMS(Normalized Least Mean Square) algorithms at MSE of -25dB.

• The Journal of the Acoustical Society of Korea
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• v.35 no.1
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• pp.55-62
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• 2016

The least-mean fourth (LMF) algorithm is well known for its fast convergence and low steady-state error especially in non-Gaussian noise environments. Recently, there has been increasing interest in the least mean square (LMS) algorithms with variable step size. It is because the variable step-size LMS algorithms have shown to outperform the conventional fixed step-size LMS in the various situations. In this paper, a variable step-size LMF algorithm is proposed, which adopts an algebraic optimal step size as a variable step size. It is expected that the proposed algorithm also outperforms the conventional fixed step-size LMF. The superiority of the proposed algorithm is confirmed by the simulations in the time invariant and time variant channels.

• The Journal of the Acoustical Society of Korea
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• v.25 no.3E
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• pp.123-130
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• 2006

The adaptive echo canceller (AEC) has become an important component in speech communication systems, including mobile station. In these applications, the acoustic echo path has a long impulse response. We propose a running-average least mean square (RALMS) algorithm with a detection method for acoustic echo cancellation. Using colored input models, the result clearly shows that the RALMS detection algorithm has a convergence performance superior to the least mean square (LMS) detection algorithm alone. The computational complexity of the new RALMS algorithm is only slightly greater than that of the standard LMS detection algorithm but confers a major improvement in stability.

• Journal of IKEEE
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• v.15 no.4
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• pp.293-298
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• 2011

In the paper, we propose a new CMF(Constant Modulus Fourth) algorithm for WCDMA(Wideband Code Multiple Access) RF(Radio Frequency) Repeater. CMF algorithm is proposed by modifying the CMA(Constant Modulus Algorithm) algorithm and improved performances are achieved by properly adjusting step size values. The steady state MSE(Mean Square Error) performance of the proposed CMF algorithm with step size of 0.35 is about 4dB better than that of the conventional CMA algorithm. And the proposed CMF algorithm requires 400~1100 less iterations than the LMS(Least Mean Square) and NLMS(Normalized Least Mean Square) algorithms at MSE of -25dB.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.2C
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• pp.150-159
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• 2002

This paper presents the convergence time, SER(Symbol Error Rate), MSE(Mean Square Error), hardware complexity and step-size(${\mu}$) about various LMS(Least Mean Square) algorithms in FS-DFE(Fractionally Spaced-Decision Feedback Equalize) for Cable Modem based on MCNS(Multimedia Cable Network System) DOCSIS(Data Over Cable Service Interface Specification) v1.0/v1.1 standards. We designed and simulated using ${SPW}^{TM}$ and synthesized using STD90 library through ${SYNOPSYS}^{TM}$. And also, we adopted the time-multiplexed multiplication and tap shared architecture in order to achieve the low hardware complexity. Simulation results show that DS-LMS algorithms[1][3] is the optimum solution about performace and hardware size. in high order QAM applications. Finally, we achieved area saving about 58% using DS-LMS algorithm compare with conventional equalizer architecture.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.3
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• pp.197-205
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• 2014

In applications of adaptive noise control or active noise control, the presence of a transfer function in the secondary path following the adaptive controller and the error path, been shown to generally degrade the performance of the Least Mean Square (LMS) algorithm. Thus, the convergence rate is lowered, the residual power is increased, and the algorithm can become unstable. In general, in order to solve these problems, the filtered-x LMS (FX-LMS) type algorithms can be used. But these algorithms have slow convergence speed and weakness in the environment that the secondary path and error path are varied. Therefore, I present the new algorithm called the "Bi-directional Filtered-x (BFX) LMS" algorithm with nearly equal computation complexity. Through experimental study, the proposed BFX-LMS algorithm has better convergence speed and better performance than the conventional FX-LMS algorithm, especially when the secondary path or error path is varied and the impulsive disturbance is flow in.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.269-273
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• 2000

This paper describes Active Noise Control (ANC) using Discrete Wavelet Transform (DWT) Domain Least Mean Square (LMS) Method. DWT-LMS is one of the transform domain input decorrelation LMS and improves the convergence speed of adaptive filter especially when the input signal is highly correlated. Conventional transform domain LMS's use Discrete Cosine Transform (DCT) because it offers linear band signal decomposition and fast transform algorithm. Wavelet transform can project the input signal into the several octave band subspace and offers more efficient sliding fast transform algorithm. In this paper, we propose Wavelet transform domain LMS algorithm and shows its performance is similar to DCT LMS in some cases using ANC simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.5
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• pp.866-874
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• 2008

Motor frequency can be measured by a hall sensor. Among the many hall sensors, a linear type hall sensor is good at high accuracy frequency measuring problem. However, in general, this linear type hall sensor has DC offset which can vary along sensor's operating voltage change. Therefore, In motor frequency measurement problem using the linear hall sensor, it needs an estimator that can estimate frequency and DC offset simultaneously. In this paper, we propose the least mean square estimator to estimate motor frequency. To verify its performance, we compare the LMS estimator with a commercial analog tachometer. Experimental results shows the proposed LMS estimator works well in varying frequency and stationary DC offset.