• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.86.4-86
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• 2002

1. Review of one dimensional M-transform 2. Definition of two dimensional(2D)M-transform 3. Properties of 2D M-transform 4. Mean, Autocorrelation 5. Crosscorrelation of input and output of a system 6. Application to fault detection of mechanical shape

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.42.5-42
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• 2002

1. Introduction for whole aspects. 2. Filtering for Fault Current Waveform 3. Estimation for relay operation. 4. Wavelet transform and ANN. 5. Identification for operated protection device. 6. Conclusion. Reference.

• Journal of IKEEE
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• v.15 no.3
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• pp.255-260
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• 2011

In this paper, we propose a parallelization technique in lane detection by using Hough transform. Hough transform has a weakness that it has a lot computation quantity, because it has to compute ${\rho}$ value in all candidate ${\Theta}$ to be detected in an image. We propose an architecture of parallel processing for this transform in a multi-core environment. The parallel processing has application to Hough transform as well as noise reduction and edge detection. This proposed architecture has 5.17 times improvement in performance compare to the existing algorithm.

• Journal of the Korean Mathematical Society
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• v.33 no.3
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• pp.541-555
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• 1996

The Fourier transform plays a central role in the theory of distribution on Euclidean spaces. Although Lebesgue measure does not exist in infinite dimensional spaces, the Fourier transform can be introduced in the space $(S)^*$ of generalized white noise functionals. This has been done in the series of paper by H.-H. Kuo [1, 2, 3], [4] and [5]. The Fourier transform $F$ has many properties similar to the finite dimensional case; e.g., the Fourier transform carries coordinate differentiation into multiplication and vice versa. It plays an essential role in the theory of differential equations in infinite dimensional spaces.

• Journal of Broadcast Engineering
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• v.15 no.3
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• pp.434-453
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• 2010

In this paper, we propose 3DTE(3-Dimensional Transform Environment) that is based on 3DT(Dimensional Transform) that performs 2-dimensional integer DCT(Discrete Cosine Transform) based on $4{\times}4$ block and 1-dimensional integer DCT based on $4{\times}1$ block after collecting same frequency coefficients in neighboring $4{\times}4$ block and supports it's additional coding tools for high performance. The transform of 3DT can keep prediction error by using $4{\times}4$ block and reduce spatial redundancy additionally. The proposed 3DTE can provide coding tools to improve the coding efficiency with using 3DT. The performance of 3DTE compared to JM11.0 is average 3.58% and 5.40% bit savings for all test sequences and HD sequences, respectively, with keeping subjective video quality in High profile.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.820-828
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• 2017

Service of digital hologram that has been recognized as a visual system for next generation requires various signal processing technologies. A transform is the most frequently used tool among signal processing techniques for 2-dimensional(D) and 3-D natural picture. A digital hologram has totally different property with a natural picture, so it is rarely efficient to apply transform tools used in 2-D image processing to a digital hologram. To overcome this a Fresnelet transform for a digital hologram has been proposed. We derive a Fresnelet transform by using the Daubechie's filter after applying an unitary Fresnel transform to a wavelet basis function. We also implement the transform as types of device and kernel code to improve operational performance. In consideration of the average time that is required for a pixel we can have observed the performance is improved up to 242 and 30 times for using the (9,7) and (5,3) filters in case of using device code.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.54.4-54
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• 2002

1.Introduction 2. Channel Equalizer Using Adaptive Neural Network 3. Data Modulation and Demodulation Using Haar Transform 4. Binary Signal Transmission Using Haar Transform 5. Conclusion

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.24-28
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• 2001

Wavelet transforms are used for implementing digital watermarking methods in the frequency domain. In this paper, we construct the digital watermarking using various wavelet transforms such as the Daubechies transform, Coiflets transform, Symlets transform and the biorthogonal transform, and we compare each digital watermarking method with the others. We investigate the preservation of the watermark after the data compression attack based on the discrete on the discrete cosine transform. We show that the biorthogonal wavelet, denoted by bior3.5, has the best performance among the wavelet types we selected in an experiment.

• Interaction and multiscale mechanics
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• v.5 no.3
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• pp.169-185
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• 2012

The concrete bridge is likely to produce fatigue cracks during long period of service due to the moving vehicular loads and the degeneration of materials. This paper deals with the time-frequency analysis of a coupled bridge-vehicle system. The bridge is modeled as an Euler beam with breathing cracks. The vehicle is represented by a two-axle vehicle model. The equation of motion of the coupled bridge-vehicle system is established using the finite element method, and the Newmark direct integration method is adopted to calculate the dynamic responses of the system. The effect of breathing cracks on the dynamic responses of the bridge is investigated. The time-frequency characteristics of the responses are analyzed using both the Hilbert-Huang transform and wavelet transform. The results of time-frequency analysis indicate that complicated non-linear and non-stationary features will appear due to the breathing effect of the cracks.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.5
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• pp.42-47
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• 2017

In the distribution of digital image, the median filtering is used for a forgery. This paper proposed the algorithm of a image forensics detection for the classification of median filtering. For the solution of this grave problem, the feature vector is composed of 42-Dim. The detected quantity 32, 64 and 128 of forgery image edges, respectively, which are processed by the Hough transform, then it extracted from the start-end point coordinates of the Hough Lines. Also, the Hough Peaks of the Angle-Distance plane are extracted. Subsequently, both of the feature vectors are composed of the proposed scheme. The defined 42-Dim. feature vector is trained in SVM (Support Vector Machine) classifier for the MF classification of the forged images. The experimental results of the proposed MF detection algorithm is compared between the 10-Dim. MFR and the 686-Dim. SPAM. It confirmed that the MF forensic classification ratio of the evaluated performance is 99% above with the whole test image types: the unaltered, the average filtering ($3{\times}3$), the JPEG (QF=90 and 70)) compression, the Gaussian filtered ($3{\times}3$ and $5{\times}5$) images, respectively.