• Journal of information and communication convergence engineering
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• v.8 no.2
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• pp.150-154
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• 2010

In this paper, the adaptive interference cancellation system (ICS) in order to cancel the feedback signal in the wireless communication system is proposed. We cancel the interference with the attenuation signal corresponding to the feedback signal and estimate the feedback signal by using Normalized Least Mean Square (NLMS) algorithm. The proposed scheme showed a better performance of interference cancellation in the measurement results.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.57-60
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• 2003

We have proposed the adaptive noise reduction algorithm using the MDFT. The algorithm proposed use the linear prediction coefficients of the AR method based on Sign algorithm that is the modified LMS instead of the least mean square(LMS). The signals with a random noise tracking performance are examined through computer simulations and confirmed that the high speed adaptive noise reduction processing system is realized with rapid convergence.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.6
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• pp.176-185
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• 1996

In this paper, we present the modified CMA (constant modulus algorithm) and LMS (least mean square) algorithms for digiCipher system with reduced hardware cost, in which the pipelined architecture is employed. They yield the performance comparable to that using floating-point operations. We show the effecstiveness of the proposed architecture through the implementation results using VHDL.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.06a
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• pp.179-180
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• 2014

The main goal of this paper is to present an adaptive filter system using NLMS(Normalized Least mean square) adaptive algorithm for noise cancellation. The proposed algorithm has less computational complexity and better convergence property than the former algorithms like spectral subtraction algorithm, etc. We use TIMIT criterion voice and Noisex-92 for the experiment. The experimental result shows the feasibility of our algorithm for filtering noise from voice effectively.

• Journal of Astronomy and Space Sciences
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• v.8 no.1
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• pp.25-51
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• 1991

The spectra of 31 Cygni were taken at the Asiage Observatory in Italy. Reduction was made using the 2nd and 4th order non-linear least square method. Spectral lines which were relatively sharp or strong were identified within the wavelength regions from 3800 to 5100$AA$. Radial velocities and equivalent widths were calculated from the Gaussian Fitting Method for this star. The measured mean radial velocity of 31 Cygni is + 0.5km/sec.

• Journal of Korean Society for Atmospheric Environment
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• v.2 no.3
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• pp.52-56
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• 1986

In this paper a adaptive LMS(least mean-square) lattice predictor, which is composed of the adaptive lattice algorithm and LMS algorithm by Widrow-Hopf, is used to predict the future air pollution of the extraordinary levels in the environmental system. This prediction algorithm is applied to the one-step forward prediction of atmospheric CO concentration by using real observed data. Computer simulation proves that the power in the forward error sequences decreases as the number of stages in the lattice is increased.

• ETRI Journal
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• v.34 no.1
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• pp.130-133
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• 2012

Recently, several noise-robust adaptive multichannel LMS algorithms have been proposed based on the spectral flatness of the estimated channel coefficients in the presence of additive noise. In this work, we propose a general form for the algorithms that integrates the existing algorithms into a common framework. Computer simulation results are presented and demonstrate that a new proposed algorithm gives better performance compared to existing algorithms in noisy environments.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1149-1152
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• 1996

Recently visual servo control is an important feature of an intelligent robot system. In this paper, we presents a Kalman filter approach for estimation of the linear optic flow model which is utilized in the visual servoing of a mobile robot. The proposed method is also compared with the conventional least mean square method via computer simulation.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.11
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• pp.93-101
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• 1997

A Hausdorff distance (HD) is one of commonly used measures for object matching. It calculates the distance between two point sets of edges in two-dimensional binary images without establishing correspondences. This paper proposes three object matching algorithm using robust HD measures based on M-estimation, least trimmed square (LTS), and .alpha.-trimmed mean methods, which are more efficient than the conventional HD measures. By computer simulation with synthetic and real images, the matching performance of the conventional HD smeasures and proposed' robust ones is compared.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.899-902
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• 1999

In this paper, we designed a equalizer that moved the multipath of channel in 8-VSB transmission receiver. After doing the initial equalization with "LMS(Least Mean Square)"aigorithm. this equalizer used "Stop-and-Go" algorithm. Because of estimating SER(Symbol to Error Ratio) every a training sequence, this can positively cope with transformation of channel and because of using fast clock than symbol-clock(10.76 MHz), we are able to reduce a multiplier.