• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.2065-2069
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• 2004

This paper presents an adaptive equalizer using finite impulse response (FIR) filter and least-mean square (LMS) algorithm. Herein, the variable step-size technique (VSLMS) for compensating the amplitude of chrominance signal is utilized. The proposed equalizer can be enhanced and compressed the chrominance signal at color subcarrier. The LMS algorithm employed in simplicity structure but gives slow convergence speed. Thus, the variable step-size is very attractive algorithm due to its computational efficiencies and the speed of convergence is improved. In addition, experimental results are carried out by using the modulated 20T sine squared test signal. It is shown here that the adaptive equalizer can be equalized the amplitude chrominance distortion in color television transmission without relative delay distortion.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.12
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• pp.12-20
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• 1993

In a conventional adaptive echo canceller, an ADF(Adaptive Digital Filter) with TDL(Tapped-Delay Line) structure modelling the echo path uses the LMS(Least Mean Square) algorithm to compute the coefficients, and NET detector using energy comparison method prevents the ADF to update the coefficients during the periods of the NET signal presence. The convergence speed of the LMS algorithm depends on the eigenvalue spread ratio of the reference signal and NET detector using the energy comparison method yields poor detection performance if the magnitude of the NET signal is small. This paper presents a new adaptive echo canceller which uses the pre-whitening filter to improve the convergence speed of the LMS algorithm. The pre-whitening filter is realized by using a low-order lattice predictor. Also, a new NET signal detection algorithm is presented, where the start point of the NET signal is detected by computing the cross-correlation coefficient between the primary input and the ADF output while the end point is detected by using the energy comparison method. The simulation results show that the convergence speed of the proposed adaptive echo canceller is faster than that of the conventional echo canceller and the cross-correlation coefficient yields more accurate detection of the start point of the NET signal.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.3
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• pp.284-292
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• 2008

The active control technique mostly uses the least-mean-square(LMS) algorithm, because the LMS algorithm can easily obtain the complex transfer function in real-time, particularly when the Filtered-X LMS(FXLMS) algorithm is applied to an active noise control(ANC) system. However, FXLMS algorithm has the demerit that stability of the control is decreased when the step size become larger but the convergence speed is faster because the step size of FXLMS algorithm is fixed. As a result, the system has higher probability which the divergence occurs. Thus the Co-FXLMS algorithm was developed to solve this problem. The Co-FXLMS algorithm is realized by using an estimate of the cross correlation between the adaptation error and the filtered input signal to control the step size. In this paper, the performance of the Co-FXLMS algorithm is presented in comparison with the FXLMS algorithm. Simulation and experimental results show that active noise control using Co-FXLMS is effective in reducing the noise in duct system.

• Proceedings of the Acoustical Society of Korea Conference
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• 1992.06a
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• pp.23-28
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• 1992

The purpose of this paper is to develop a new adaptive echo canceller improving convergence speed and near-end-talker detection performance of the conventional echo canceller. In a conventional adaptive echo canceller, an adaptive digital filter with TDL(Tapped-Delay Line) structure modelling the echo path uses the LMS(Least Mean Square) algorithm to cote the coefficients, and NET detector using energy comparison method prevents the adaptive digital filter to update the coefficients during the periods of the NET signal presence. The convergence speed of the LMS algorithm depends on the eigenvalue spread ratio of the reference signal and NET detector using the energy comparison method yields poor detection performance if the magnitude of the NET signal is small. This paper presents a new adaptive echo canceller which uses the pre-whitening filter to improve the convergence speed of the LMS algorithm. The pre-whitening filter is realized by using a low-order lattice predictor. Also, a new NET signal detection algorithm is presented, where the start point of the NET signal is detected by computing the cross-correlation coefficient between the primary input and the ADF(Adaptive Digital Filter) output while the end point is detected by using the energy comparison method. The simulation results show that the convergence speed of the proposed adaptive echo canceller is faster than that of the conventional echo canceller and the cross-correlation coefficient yield more accurate detection of the start point of the NET signal.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.598-603
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• 2007

The active control technique mostly uses the Least-Mean-Square (LMS) algorithm, because the LMS algorithm can easily obtain the complex transfer function in real-time, particularly when the Filtered-X LMS (FXLMS) algorithm is applied to an active noise control (ANC) system. However, FXLMS algorithm has the demerit that stability of the control is decreased when the step size become larger but the convergence speed is faster because the step size of FXLMS algorithm is fixed. As a result, the system has higher probability which the divergence occurs. Thus the Co-FXLMS algorithm was developed to solve this problem. The Co-FXLMS algorithm is realized by using an estimate of the cross correlation between the adaptation error and the filtered input signal to control the step size. In this paper, the performance of the Co-FXLMS algorithm is presented in comparison with the FXLMS algorithm. Simulation results show that active noise control using Co-FXLMS is effective in reducing the noise in duct system.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.12
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• pp.57-63
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• 2002

In this paper, the feedforward control with least mean square (LMS) adaptive algorithm is proposed and examined to reduce rotating error by runout of an active magnetic bearing system. Using eddy-current type gap sensor fur control, the electrical runout caused by non-uniform material properties of sensor target produces rotational error amplified in feedback control loop, so this runout should be eliminated to increase rotating accuracy. The adaptive feedforward controller is designed and examined its tracking and stability performances numerically with established frequency response function. The tested grinding spindle system is manufactured with a 5.5 ㎾ internal motor and 5-axis active magnetic bearing system including 5 eddy current gap sensors which have approximately 15 ~ 30 ${\mu}{\textrm}{m}$ of electrical runout. According to the experimental analysis, the error signal in radial bearings is reduced to less than 5 ${\mu}{\textrm}{m}$ when it is rotating up to 50,000 rpm due to applying the feedforward control for first order harmonic frequency, and vibration of the spindle base is also reduced about same frequency.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.1
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• pp.27-35
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• 2005

Ultrasonic inspection methods are widely used for detecting flaws in materials. The signal analysis step plays a crucial part in the data interpretation process. A number of signal processing methods have been proposed to classify ultrasonic flaw signals. One of the more popular methods involves the extraction of an appropriate set of features followed by the use of a neural network for the classification of the signals in the feature spare. This paper describes an alternative approach which uses the least mean square (LMS) method and exportation maximization (EM) algorithm with the model based deconvolution which is employed for classifying nondestructive evaluation (NDE) signals from steam generator tubes in a nuclear power plant. The signals due to cracks and deposits are not significantly different. These signals must be discriminated to prevent from happening a huge disaster such as contamination of water or explosion. A model based deconvolution has been described to facilitate comparison of classification results. The method uses the space alternating generalized expectation maximiBation (SAGE) algorithm ill conjunction with the Newton-Raphson method which uses the Hessian parameter resulting in fast convergence to estimate the time of flight and the distance between the tube wall and the ultrasonic sensor. Results using these schemes for the classification of ultrasonic signals from cracks and deposits within steam generator tubes are presented and showed a reasonable performances.

• The Journal of the Acoustical Society of Korea
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• v.40 no.1
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• pp.46-54
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• 2021

In this paper, active noise control was performed to reduce radiated noise in the low frequency band of dishwashers. First, through an analysis of the noise environment of the dishwasher, it was confirmed that the pump noise contributed the most to the radiated noise in the low frequency band, From the result of the noise environment analysis, the reference signal was selected to be the vibration signal of the pump body. The reference signal was obtained by using the accelerometer on the pump body, which can prevent acoustic feedback. The error signal sensor was selected as a microphone located at 1 m in front of the dishwasher and 0.5 m in height. And to design the controller, the error signal and the reference signal were measured at the operational rpms of the dishwasher at 2,500 rpm, 2,600 rpm and 2,800 rpm, and the secondary path transfer function was measured. The designed controller was mounted on Digital Signal Processor (DSP) equipment, and the control performance was verified experimentally. As a result of the measurement at the 3 operational rpms, the 7th multiple component of pump operating frequency decreased by 1.93 dB, 4.43 dB, 5.15 dB per rpm, and the 12th multiple component decreased by 6.67 dB, 2.34 dB, 4.28 dB per rpm. And overall Sound Pressure Level (SPL) decreased by 0.84 dB, 2.58 dB, 1.48 dB by rpm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.10B
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• pp.1210-1215
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• 2011

In this paper, a supervised adaptive equalization algorithm based on probability density function (PDF) matching method is introduced and its decision-feedback version is proposed for underwater communication channels with strong impulsive noise and severe multipath characteristics. The conventional least mean square (LMS) algorithm based on mean squared error (MSE) criterion has shown to be incapable of coping with impulsive noise and multipath effects commonly shown in underwater communications. The linear PDF matching algorithm, which shows immunity to impulsive noise, however, has revealed to yield unsatisfying performance under severe multipath environments with impulsive noise. On the other hand, the proposed nonlinear PDF matching algorithm with decision feedback proves in the simulation to possess superior robustness against impulsive noise and multipath characteristics of underwater communication channels.

• Proceedings of the IEEK Conference
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• 2000.06b
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• pp.238-241
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• 2000

This paper describes an equalizer using the DFE (Decision Feedback Equalizer) structure, CMA. (Constant Modulus Algorithm) and LMS (Least Mean Square) algorithms. We employ high speed multipliers, square logics and many CSAs (Carry Save Adder) for high speed operations. We have developed floating-point models and fixed-point models using the COSSAP$\^$TM/ CAD tool and developed VHDL models. We have peformed logic synthesis using the SYNOPSYS$\^$TM/ CAD tool and the SAMSUNG 0.5 $\mu\textrm{m}$ standard cell library (STD80). The total number of gates is about 130,000.