• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.58-63
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• 1998

B.Widrow established fundamental relations between the least-mean-square (LMS) algorithm and the digital Fourier transform［1］. By extending these relations, we proposed the short time spectra analysis system using the LMS algorithm［2]. In that paper, we used the normal LMS algorithm on the thought of dealing with only real analytical signal. This algorithm minimizes the real mean-square by recursively altering the complex weight vector at each sampling instant. But, the short time spectra analysis sometimes deals with the complex signal that is outputted from complex analog filter. So, in order to optimize and develop this methods, furthermore it is necessary to derive an algorithm for the complex analytical signal. In this paper, we first discuss the new adaptive system for the spectra analysis using the complex LMS algorithm and then derive convergence condition, time constant of coefficient adjustment and frequency resolution by extending the discussion. Finally, the effectiveness of the proposed method is experimentally demonstrated by applying it to the measurement of transfer performance on complex analog filter.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.2
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• pp.128-132
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• 2011

Least mean square adaptive algorithms have played important role in radar, sonar, speech processing, and mobile communication. In mobile communication area, the convergence rate of a LMS algorithm is quite important. However, LMS algorithms have slow and non-uniform convergence rate problem For overcoming these shortcomings, various variable step LMS adaptive algorithms have been studied in recent years. Most of these recent LMS algorithms have used complex variable step methods to get a rapid convergence. But complex variable step methods need a high computational complexity. Therefore, the main merits such as the simplicity and the robustness in a LMS algorithm can be eroded. The proposed deterministic variable step LMS algorithm is based upon a simple deterministic function for the step update so that the simplicity of the proposed algorithm is obtained and the fast convergence is still maintainable.

• Journal of Digital Contents Society
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• v.5 no.4
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• pp.295-299
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• 2004

In this paper, we compare and analyze the LMS ard RLS algorithm of IEEE802.15.3(HDR-WPAN) system. The LMS algorithm have two merits that easily embody and not complex, but convergence speed is slow. The RLS algorithm have fast convergence speed, but very complex. When equalization using LMS algorithm, it can achieve adaptive equalization after 250 sample in fading environment, but case of RLS algorithm can achieve adaptive equalization after just 50 sampls. The computer simulation proved that adaptive equalizer to fast equalization and stability of HDR-WPAN system is more effective using RLS algorithm then LMS algorithm.

• 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.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.9
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• pp.37-43
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• 2010

An Interference Cancellation Wireless Repeater transmitts directly amplified the RF signal input to extend the coverage of the base station. Such a repeater inevitably suffers from the feedback interferences due to the environment and the adaptive Interference Cancelling System(ICS) is necessary. In this paper, the Variable Stepsize Complex Sign -Sign(VSCSS) LMS algorithm for ICS is presented. The algorithm can be implemented without multiplication/division arithmetic operation so that the required logic resources can be dramatically reduced in FPGA implementation. The performance of the proposed algorithm was analyzed in comparison with CSS-LMS algorithm and the learning curves obtained from simulation showed an excellent agreement with the theorical prediction. The simulation result with ICS in fading feedback channel environment showed the performance of the proposed algorithm is competible with NLMS algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.173-176
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• 1996

The transient behavior of the complex-LMS adaptive filter is studied when the adaptive filter is operating on a fixed or sweeping complex frequency sine-wave signal. The first-order difference equation is derived for the mean weights and its closed form solution is obtained. The transient response is represented as a function of the eigenvectors and eigenvalues of input correlation matrix. The mean-square error of the algorithm is evaluated as well. An optimal convergence parameter and filter length can be determined for sweeping frequency sine-wave signals as a function of frequency change rate and signal and noise powers.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.11
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• pp.8-15
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• 1992

This paper analyzes the properties of such algorithm that corresponds to the LMS algorithm with additional update terms, parameterized by the scalar factors $\alpha$ and $\beta$, and presents its structure. The analysis of convergence leads to complex eigenvalues of the transition matrix for the mean weight vector. Regions in which the algorithm becomes stable are demonstrated. The computational cmomplexities of MLMS algorithms are compared with those of MADF, sign and the conventional LMS algorithms. In application of the system identification the second order momentum MLMS algorithm has faster convergence speed than LMS and the first order MLMS algorithms.

• The Journal of the Acoustical Society of Korea
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• v.16 no.3
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• pp.38-44
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• 1997

In this study, wer derived LMF-Sato, LMSF-Sato complex blind equalization algorithms for complex data. And then, the convergence rates, the convergence characteristics at the steady state and the stability of the proposed LMF and LMSF blind equalization algorithms are compared with those of LMS-Sato blind equalization algorithm. In simulations with 16-QAM data, LMF-Sato and LMSF-Sato algorithms showed better performance comparing with LMS-Sato algorithm generally. When the initial estimation errors of the weights of the equalizer are large, LMF-Sato algorithm showed ill characteristic in stability. However, LMSF-Sato algorithm has good covergence characteristics and preserves robustness.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.6
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• pp.183-189
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• 2003

The study of the automotive noise reduction has been concentrated on the reduction of the automotive engine noise because the engine noise is the major cause of automotive noise. However, many studies of automotive engine noise led to the interest of the noise reduction of the exhaust and intake system. Recently, the active control method is used to reduce the noise of an automotive exhaust and intake system. It is mostly used the LMS(Least-Mean-Square) algorithm as an algorithm of active control because the LMS algorithm can easily obtain the complex transfer function in real-time. Especially, Filtered-X LMS (FXLMS) algorithm is applied to an Active Noise Control system. However, the convergence performance of LMS algorithm went bad when the FXLMS algorithm was applied to an active control of the induction noise under rapidly accelerated driving conditions. So, in order to solve this problem, the modified FXLMS algorithm is proposed. In this study, the improvement of the control performance using the modified FXLMS algorithm under rapidly and suddenly accelerated driving conditions was identified. Also, the performance of an active control using the LMS algorithm under rapidly accelerated driving conditions was evaluated through the theoretical derivation using a chirp signal to have similar characteristics with the induction noise signal.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.10
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• pp.2579-2585
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• 1996

In this paper, a complex fuzzy adaptive decision feedback equalizer(CFADFE) based on the LMS algorithm is proposed. The propoed equalizer is based on the complex fuzzy adaptive equalizer. The CFADFE isconstructed from a set of changeable complex fuzzy IF-THEN rules, where the 'IF' part of the rule is characterized by the state from a set of changealble complex fuzzy IF-THEN rules, where the 'IF' part of the rule is characterized by the state of the desision feedback. the role of decision feedback is to reduce the computational complexity. Computer simulation of the decision feedback. The role of decision feedback is to reduce the computational complexity. Computer simulation shosw that the CFADFE notonly reduces the computational complexity but also improves the performance compared with the conventional complex fuzzy adaptive equalizers. We also show that the adaptation speed is greatly improved by incorporating some linguistic information about the channel into the equalzer. It is applied to M-ary QAM digital communication system with linear and nonlinear complex channel characteristics.