• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.269-273
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• 2000

This paper describes Active Noise Control (ANC) using Discrete Wavelet Transform (DWT) Domain Least Mean Square (LMS) Method. DWT-LMS is one of the transform domain input decorrelation LMS and improves the convergence speed of adaptive filter especially when the input signal is highly correlated. Conventional transform domain LMS's use Discrete Cosine Transform (DCT) because it offers linear band signal decomposition and fast transform algorithm. Wavelet transform can project the input signal into the several octave band subspace and offers more efficient sliding fast transform algorithm. In this paper, we propose Wavelet transform domain LMS algorithm and shows its performance is similar to DCT LMS in some cases using ANC simulation.

• Journal of Biomedical Engineering Research
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• v.17 no.3
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• pp.347-354
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• 1996

This paper presents digital hearing aids signal processing system in WT(wavelet transform) domain. For implementation of hearing aids in WT domain, the gain in frequency domain is approximated in WT domain. We also present the gain selection algorithm to deal with the change of input signal power. Most transform methods produce blocking effect, and this effect degrades the convergence rate of feedback canceller. As a solution, we proposed wavelet transform bascd feedback canceller. To evaluate the performance, we compared it with LOT (lapped orthogonal transform) method in the frequency domain. This system has not shown the blocking effect, and improves convergence rate as compared with the LOT based feedback canceller.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.1020-1026
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• 2016

Motion estimation (ME) algorithms supporting quarter-pixel accuracy have been recently introduced to retain detailed motion information for high quality of video in the state-of-the-art video compression standard of H.264/AVC. Conventional sub-pixel ME algorithms in the spatial domain are faced with a common problem of computational complexity because of embedded interpolation schemes. This paper proposes a low-complexity sub-pixel motion estimation algorithm in the transform domain utilizing shifting matrix. Simulations are performed to compare the performances of spatial-domain ME algorithms and transform-domain ME algorithms in terms of peak signal-to-noise ratio (PSNR) and the number of bits per frame. Simulation results confirm that the transform-domain approach not only improves the video quality and the compression efficiency, but also remarkably alleviates the computational complexity, compared to the spatial-domain approach.

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.125-133
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• 1996

In this paper, we dicuss on the properties related to the circular filtering in orthogonal transform domain. The efficient filtering schemes in six orthogonal transform domains are presented by generalizing the convolution-multiplication property of the DFT. In brief, the circular filtering can be accomplished by multiplying the transform domain filtering matrix W, which is shown to be very sparse, yielding the computational gains compared with the time domain processing. As an application, decimation and interpolation techniques in orthogonal transform domains are also investigated.

• Communications of the Korean Mathematical Society
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• v.11 no.4
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• pp.975-981
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• 1996

Let $D \subset C^2$ be a bounded convex domain with real analytic boundary. We get some Lipschitz regularity of the Cauchy transform on the convex domain D.

• The Journal of the Acoustical Society of Korea
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• v.31 no.5
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• pp.332-339
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• 2012

Beamspace transform algorithm transforms spatial-domain data - such as x, y, z dimension - into incidence-angle-domain data, which is called beamspace-domain data. The beamspace transform method is generally used in source localization and tracking, and adaptive beamforming problem. When the beamspace transform method is used in multichannel audio source separation, the inverse beamspace transform is also important because the source image have to be reconstructed. This paper studies the beamspace transform and inverse transform algorithms for multichannel audio source separation system, especially for the beamspace-domain multichannel NMF algorithm.

• Proceedings of the IEEK Conference
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• summer
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• pp.274-275
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• 2004

The Hough transform has been used as a tool for line detection. The main idea of the Hough transform is to transform each pixel in the image individually into the parameter domain. In this way, the Hough transform converts a difficult global detection problem in the image domain into a more easily solved local peak detection problem in the parameter domain. In this paper, we show that the discrete Hough transform is identical to the discrete Radon transform. Thus, we can use the generalized Radon transform to handle more general parameterized curve types.

• Journal of the Korean Society for Railway
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• v.9 no.2 s.33
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• pp.187-192
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• 2006

The regularity of railway track alignment is a crucial component fur maintaining travel safety and the smoothness of passenger ride. The conventional spectral analysis has been considered to estimate the severity of the track irregularity from measured data. The time domain data used to be changed into the frequency domain by Fourier transform. Because the measuring points can be regarded as the time points, the spatial-frequency can be introduced instead of the time-frequency. Although FFT(Fast Fourier Transform) and/or PSD(Power Spectral Density) function could provide fairly localized information within frequency domain, but chronical configurations of data could be missed. In this study, we attempt to apply the Morlet wavelet transform for the purpose of a frequency-time-domain analysis rather than a frequency-domain analysis. The applicability of wavelet transform is examined for the estimation of the track irregularity with real measured track data on the section of Kyoung-bu line by EM-120 measuring vehicle. It is shown that the wavelet transform can be an effective tool to manage the track irregularity.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.9
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• pp.1188-1197
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• 1995

This paper describes an algorithm that reduces computational requirement of the Kalman filter and estimates the signal efficiently. The reference signals are mapped onto the orthogonal wavelet transform domain so that the eigenvalue spread of its autocorrelation matrix could be smaller than that in the time domain. In the wavelet transform domain the autocorrelation matrix is nearly diagonal. Therefore, the transformed signal can be decomposed each orthogonal elements. The Kalman filter can be applied to each orthogonal elements and computational requirement is reduced. The possibility of applying the parallel Kalman filter was verified through the theory and simulation. The eigenvalue spread in the wavelet transform domain is smaller 8.35 times than that in the time domain and the computational requirement is reduced from 1.4 times to 2. 93 times than that of the conventional Kalman filter.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.44-48
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• 2009

This paper develops a methodology for resizing image resolutions in an arbitrary block transform domain. To accomplish this, we represent the procedures resizing images in an arbitrary transform domain in the form of matrix multiplications from which the matrix scaling the image resolutions is produce. The experiments showed that the proposed method produces the reliable performances without increasing the computational complexity, compared to conventional methods when applied to various transforms.