• The Journal of the Acoustical Society of Korea
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• v.18 no.7
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• pp.45-55
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• 1999

In this paper, we used the WLMS(Wavelet domain Least Mean Square) adaptive filter based on the wavelet transform to cancel grain noise. Usually, grain noise occurs in changes of the crystalline structure of metals in high temperature environment. It makes the detection of flaw difficult. The WLMS adaptive filtering algorithm establishes the faster convergence rate by orthogonalizaing the input vector of adaptive filter as compared with that of LMS adaptive filtering algorithm in time domain. We implemented the WLMS adaptive filter by using the delayed version of the primary input vector as the reference input vector and then implemented the CA-CFAR(Cell Averaging- Constant False Alarm Rate) threshold estimator. CA-CFAR threshold estimator enables to detect the flaw and back echo signals automatically. Here, we used the output signals of adaptive filter as its input signal. To Cow the statistical characteristic of ultrasonic signals corrupted by grain noise, we performed run test. The results showed that ultrasonic signals are nonstationary signal, that is, signals whose statistical properties vary with time. The performance of each filter is appreciated by the signal-to-noise ratio. After LMS adaptive filtering in time domain, SNR improves to about 2-3㏈ but after WLMS adaptive filtering in wavelet domain, SNR improves to about 4-6㏈.

• The Korean Journal of Applied Statistics
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• v.23 no.1
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• pp.151-165
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• 2010

Images are often corrupted by impulse noise due to a noise sensor or channel transmission errors. The filter based on SVM(Support Vector Machine) and the improved adaptive median filtering is proposed to preserve image details while suppressing impulse noise for image restoration. Our approach uses an SVM impulse detector to judge whether the input pixel is noise. If a pixel is detected as a noisy pixel, the improved adaptive median filter is used to replace it. To demonstrate the performance of the proposed filter, extensive simulation experiments have been conducted under both salt-and-pepper and random-valued impulse noise models to compare our method with many other well known filters in the qualitative measure and quantitative measures such as PSNR and MAE. Experimental results indicate that the proposed filter performs significantly better than many other existing filters.

• Communications for Statistical Applications and Methods
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• v.18 no.6
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• pp.871-886
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• 2011

This paper proposes a powerful SVM-ASM filter, the adaptive switching median(ASM) filter based on support vector machines(SVMs), to effectively reduce impulse noise in corrupted images while preserving image details and features. The proposed SVM-ASM filter is composed of two stages: SVM impulse detection and ASM filtering. SVM impulse detection determines whether the pixels are corrupted by noise or not according to an optimal discrimination function. ASM filtering implements the image filtering with a variable window size to effectively remove the noisy pixels determined by the SVM impulse detection. Experimental results show that the SVM-ASM filter performs significantly better than many other existing filters for denoising impulse noise even in highly corrupted images with regard to noise suppression and detail preservation. The SVM-ASM filter is also extremely robust with respect to various test images and various percentages of image noise.

• Journal of Power System Engineering
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• v.18 no.5
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• pp.129-136
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• 2014

This paper proposes improvement on sensorless vector control performance of a permanent magnet synchronous motor (PMSM) with sliding mode observer. An adaptive observer gain and second order cascade low-pass filter (LPF) were used to improve the estimation accuracy of the rotor position and speed. The adaptive observer gain was applied to suppress the chattering intensity and obtained by using the Lyapunov's stability criterion. The second order cascade LPF was designed for the system to escalate the filtering performance of the back-emf estimation. Furthermore, genetic algorithm was used to optimize the system PI controller's performance. Simulation results showed the effectiveness of the suggested improvement strategy. Moreover, the strategy was useful for the sensorless vector control of PMSM to operate on the low-speed area.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.917-922
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• 1992

Resently there have been increasing interests in adaptive identification and control of flexible structures. In this paper, vector channel lattice filters and their applications to parameter identification of flexible structures are studied. Numerical examples are given to show its performace to estimate the natural frequencies of 5-mass system. It is observed that vector channel lattice filter convetges quickly and identifies modal frequencies even when some of them is unobservable for some measurements. Experimental results demonstrated the ability of the lattice filter to identify the natural frequencies and the damping ratios of cantilever beam and pipe.

• Journal of KIISE:Software and Applications
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• v.35 no.3
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• pp.162-168
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• 2008

A look-up table based vector adaptive filter is proposed in color inverse halftoning. Inverse halftoning converts halftone image into a continuous-tone image. The templates and training images are required in the process of look-up table based methods, which can be obtained from distributed patterns in the sample halftone images and their original images. Although the look-up table based methods usually are faster and show better performances in PSNR than other methods do, they show wide range of qualities depending on how they treat nonexisting patterns in the look-up table. In this paper, a vector adaptive filter is proposed to compensate for these nonexisting patterns, which achieves better quality owing to the contributed informations about hue, saturation, and intensity of surrounding pixels. The experimental results showed that the proposed method resulted in higher PSNR than that of conventional Best Linear Estimation method. The bigger the size of the template in the look-up table becomes, the more outstanding quality in the proposed method can be obtained.

• Journal of Information Processing Systems
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• v.7 no.1
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• pp.103-110
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• 2011

In this paper, an adaptive motion vector smoothing scheme based on weighted vector median filtering is proposed in order to eliminate the motion outliers more effectively for improving the quality of side information in frame-based distributed video coding. We use a simple motion vector outlier reliability measure for each block in a motion compensated interpolated frame and apply weighted vector median filtering only to the blocks with unreliable motion vectors. Simulation results show that the proposed adaptive motion vector smoothing algorithm improves the quality of the side information significantly while maintaining low complexity at the encoder in frame-based distributed video coding.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.677-680
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• 1998

In this paper, we proposed a lwo bit rate subband coding with adaptive vector quantization using the correlation between motion vector and block energy in subband. In this method, the difference between the input signal and the motion compensated interframe prediction signal is decomposed into several narrow bands using quadrature mirror filter (QMF) structure. The subband signals are then quantized by adaptive vector quantizers. In the codebook generating process, each classified region closer to the block value in the same region after the classification of region by the magnitude of motion vector and the variance values of subband block. Because codebook is genrated considering energy distribution of each region classified by motion vector and variance of subband block, this technique gives a very good visual quality at low bit rate coding.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.1
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• pp.45-54
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• 2019

The damage detection method using the extended Kalman filter(EKF) technique has been continuously used since EKF can estimation the responses of the damaged building structure and the stiffness of the structure. However, in the use of EKF, the requirement of setting the initial paramters P, Q, and R has caused the divergence and instability of the state vector, and various researches have been conducted to determine theses parameters. In this paper, adaptive extended Kalman filter(AEKF) method is proposed to solve the problem of setting the values of P, Q, and R, which are important parameters determining the convergence performance of the EKF state vector. By using the AEKF method proposed in this study, the P, Q, and R parameters are updated every k steps. The proposed algorithm is applied for the estimation of stiffness and the damage detection of 3-DOF problem. Based of the verification, it can be found that the selection process for the values of P, Q, and R can improve the convergence performance of EKF.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.98.5-98
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• 2001

An efficient adaptive nonlinear compensator, based on a wavelet transform domain adaptive Volterra filter along with a modified escalator algorithm, is proposed to speed up the convergence rate of an adaptive LMS algorithm. In particular, it is well known that the e.g., slow convergence speed of an adaptive LMS algorithm depends on the statistical characteristics (e.g., large eigenvalue spread) of the corresponding auto-correlation matrix of the input vector. To solve such a convergence problem, the proposed approach utilizes a modified escalator algorithm and a wavelet transform domain adaptive LMS Volterra filtering technique, which leads to diagonalization of the auto-correlation matrix of the ...