• Journal of Sensor Science and Technology
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• v.9 no.4
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• pp.316-326
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• 2000

A new signal processing algorithm for white light interferometry has been proposed and investigated theoretically. The goal of the algorithm is to determine the absolute optical path length of an interferometer with very high precision (<< one optical wavelength). The algorithm features cross-correlation of interferometer fringe scans and hypothesis testing. The hypothesis test looks for a zero order fringe peak candidate about which the cross-correlation is symmetric minimizing the uncertainty of misidentification. The shot noise limited performance of the proposed signal processing algorithm has been analyzed using computer simulations. Simulation results were extrapolated to predict the misidentification rate at Signal to-Shot noise ratio (SNR) higher than 31 dB. Root-mean-square phase error between the computer-generated zero order fringe peak and the estimated zero order fringe peak has been calculated for the changes of three different parameters (SNR, fringe scan sampling rate, coherence length of light source). Results of computer simulations showed the ability of the proposed signal processing algorithm to identify the zero order fringe peak correctly. The proposed signal processing algorithm uses a software approach, which is potentially inexpensive, simple and fast.

• The Journal of the Acoustical Society of Korea
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• v.20 no.5
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• pp.28-34
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• 2001

In stereo acoustic echo canceller scheme, coefficients of adaptive filter converge very slowly or misconverge to real acoustic echo path in receiving room. This is due to cross-correlation in stereo signals. In this paper, a new preprocess algorithm is proposed to improve the performance of stereo AEC(acoustic echo canceller) without computational burden. The proposed algorithm reduces cross-correlation using Gram-Schmidt orthogonality principles and nonlinear filtering. Computer simulations demonstrate that this algorithm performs well compared to conventional ones. When the acoustic path of transmitting room is changed, stereo AEC using proposed algorithm is well performed.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.10
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• pp.639-642
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• 2005

In this paper, a robust nonlinear echo cancellation is proposed, where a third-order adaptive Volterra filtering is employed along with an expanded correlation LMS (ECLMS) algorithm to compensate for nonlinear distortion in the echo path. (e.g., DAC of the hybrid network). Finally, the robustness in the echo cancellation of the proposed approach is demonstrated using computer simulations, where high attenuation of echo signals is achieved even in the double-talk situation (e.n., BdB improvement in ERLE).

• 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 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.32 no.12
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• pp.1039-1047
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• 2015

Contact type sensors (e.g., displacement sensor and strain gauge) were typically used to evaluate the safety and mechanical properties in machines and construction. However, those contact type sensors have been constrained because of measurement problems such as surface roughness, temperature, humidity, and shape. The Digital Image Correlation (DIC) measurement system is a vision measurement system. This measurement system uses the taken image using a CCD camera and calculates the image correlation between the reference image and the deformed image under external force to measure the displacement and strain rates. In this paper, we discuss methods to improve the measurement precision of the digital image correlation measurement system. A tensile test was conducted to compare the precision improvement effects, by using the universal test machine and the DIC measurement system, with the use of subpixel algorithms, i.e., the Coarse Fine Search (CFS) algorithm and the Peak Finding (PF) algorithm.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.1
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• pp.77-85
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• 2018

This paper proposes a robust digital video stabilization algorithm to extract and track an object, which uses a phase correlation-based motion correction. The proposed video stabilization algorithm consists of background stabilization based on motion estimation and extraction of a moving object. The motion vectors can be estimated by calculating the phase correlation of a series of frames in the eight sub-images, which are located in the corner of the video. The global motion vector can be estimated and the image can be compensated by using the multiple local motions of sub-images. Through the calculations of the phase correlation, the motion of the background can be subtracted from the former frame and the compensated frame, which share the same background. The moving objects in the video can also be extracted. In this paper, calculating the phase correlation to track the robust motion vectors results in the compensation of vibrations, such as movement, rotation, expansion and the downsize of videos from all directions of the sub-images. Experimental results show that the proposed digital image stabilization algorithm can provide continuously stabilized videos and tracking object movements.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.737-742
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• 2007

The method of the reducing duct noise can be classified by passive and active control techniques. However, passive control has a limited effect of noise reduction at low frequencies (below 500Hz) and is limited by the space. On the other hand, active control can overcome these passive control limitations. 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, the convergence performance of the LMS algorithm decreases slightly so it may delay the convergence time when the FXLMS algorithm is applied to the active control of duct noise. Thus the Co-FXLMS algorithm was developed to improve the control performance in order 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 duct noise.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.1051-1054
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• 1988

In this paper we present initial convergence properties of the Kalman filtering algorithm, we put an arbitrary small positive correlation matrix as an initial condition in the recursive algorithm. This arbitrary small initial condition perturbs the Kalman filtering algorithm and may lead to initial instability. We derive a condition which insures the stable operation of the Kalman filtering algorithm from the stochastic Lyapunov difference equation.

• Journal of Biomedical Engineering Research
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• v.23 no.2
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• pp.101-107
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• 2002

This paper presents a segmentation algorithm to extract endocardial contour and epicardial contour of left ventricle in MR Cardiac images. The algorithm is based on a generalized gradient vector flow(GGVF) snake and a prediction of initial contour(PIC). Especially. the proposed algorithm uses physical characteristics of endocardial and epicardial contours, cross profile correlation matching(CPCM), and a mixed interpolation model. In the experiment, the proposed method is applied to short axis MR cardiac image set, which are obtained by Siemens, Medinus, and GE MRI Systems. The experimental results show that the proposed algorithm can extract acceptable epicardial and endocardial walls. We calculate quantitative parameters from the segmented results, which are displayed graphically. The segmented left vents role is visualized volumetrically by surface rendering. The proposed algorithm is implemented on Windows environment using Visual C ++.