• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.49-51
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• 1996

The z-transform method is a basic mathematical tool in analyzing and designing sampled-data control systems. However, since the z-transform method relates only the sampling-instants signals, another mathematical tool is necessary to describe the continous signals between the sampling instants. For this purpose the delayed and the modi fled z-transform methods were developed. The definition of the modi fled z-transform includes a sample in the interval [-T,0] of the original signal in its series expression, where the signal value is always zero for any physical system. From this reason one step skew of the time index always appears in its application formulas. This introduces an unnecessary operation and a gap in linking the mathematical formula and its physical interpretation. Considering the conceptual difficulty and application inconvenience, a method of using the advanced z-transform in analysis of sampled-data control systems is developed as a replacement of the modi fled z-transform. With one formulation of the advanced z-transform, now it is possible to relate both the signals of the sampling instants and those in between without any complication and conceptual difficulty.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.694-696
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• 2001

인터넷상에서 메시지 교환을 위하여 XML의 사용이 급증함에 따라 XML문서의 보안이 필요하게 되었고, 이에 W3C는 XML-Signature 표준안을 제안 하고 있다. XML-Signature 표준 스펙에서는 서명할 문서의 내용을 선택 하는 방법으로 Transform 알고리즘들을 제안하고 있고, 그 알고리즘들은 서명자가 원하는 문서의 일부분만을 선택하거나, 변형하는 방법들을 기술하고 있다. 서명 시스템은 그런 Transform 알고리즘을 사용하여 문서의 전체 흑은 원하는 부분만을 선택하여 서명 함으로써 서명의 생성 및 검증의 처리속도를 높일 수 있고, 송.수신 시 효율을 높일 수 있고, 기존의 문서를 재사용 할 수 있는 등의 장점을 제공 하고 있다. 본 논문에서는 위와 같은 처리를 할 수 있는 4가지 Transform 알고리즘(XPath, XSLT, Enveloped. Base64 Transform)과 XML문서들의 무결성을 유지하기 위해 W3C의 Canonical XML 스펙을 기반으로 하는 Canonicalization Transform 알고리즘을 설계, 구현하였다. 이 Transform 알고리즘들은 XML 디지틸 서명 뿐 만 아니라 문서를 선택적으로 변환하는 응용등에서 사용할 수 있다.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.438-450
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• 2003

Spatial joins find pairs of objects that overlap with each other. In spatial joins using indexes, original-space indexes such as the R-tree are widely used. An original-space index is the one that indexes objects as represented in the original space. Since original-space indexes deal with sizes of objects, it is difficult to develop a formal algorithm without relying on heuristics. On the other hand, transform-space indexes, which transform objects in the original space into points in the transform space and index them, deal only with points but no sites. Thus, spatial join algorithms using these indexes are relatively simple and can be formally developed. However, the disadvantage of transform-space join algorithms is that they cannot be applied to original-space indexes such as the R-tree containing original-space objects. In this paper, we present a novel mechanism for achieving the best of these two types of algorithms. Specifically, we propose a new notion of the transform-space view and present the transform-space view join algorithm(TSVJ). A transform-space view is a virtual transform-space index based on an original-space index. It allows us to interpret on-the-fly a pre-built original-space index as a transform-space index without incurring any overhead and without actually modifying the structure of the original-space index or changing object representation. The experimental result shows that, compared to existing spatial join algorithms that use R-trees in the original space, the TSVJ improves the number of disk accesses by up to 43.1% The most important contribution of this paper is to show that we can use original-space indexes, such as the R-tree, in the transform space by interpreting them through the notion of the transform-space view. We believe that this new notion provides a framework for developing various new spatial query processing algorithms in the transform space.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.3
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• pp.540-545
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• 2013

The Fractional Fourier transform, as a generalization of the classical Fourier Transform, was first introduced in quantum mechanics. Because of its simple and useful properties of Fractional Fourier transform in time-frequency plane, various research results in sonar and radar signal processing have been introduced and shown superior results to conventional method utilizing Fourier transform until now. In this paper, we applied Fractional Fourier transform to sonar signal processing to detect and separate the overlapping linear frequency modulated signals. Experimental results show that received overlapping LFM(Linear Frequency Modulation) signals can be detected and separated effectively in Fractional Fourier transform domain.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.1
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• pp.39-44
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• 2013

In this paper digital phase-shifter for multi-arm spiral antennas was designed by using Hilbert transform. All frequency components in input signal are phase-shifted for 90 degree by Hilbert transform, and the transform is implemented by FIT and IFIT. Digital phase-shifter generates two signals with phase difference of 90 degree by using Hilbert transform from input signals sampled by analog-digital converter(ADC), and then the input signal is phase-shifted for a given phase by using two signals. Hilbert transform based on digital phase-shifter is designed by Xilinx System generator, and the effects of input noise, FIT point, sampling period, initial phase of input signal, and shifted phase are simulated and its results are compared with Matlab results.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.243-250
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• 1999

We consider $Y=X{\lambda}Z,\;{\lambda}>0$, where X and Z are independent random variables, and Y is the length biased distribution or the equilibrium distribution of X. The purpose of this paper is to consider the distribution of X or Y when the distribution of Z is given and the distribution of Z when the distribution of X or Y is given, In particular, we obtain that the necessary and sufficient conditions for X to be $X^{2}({\upsilon})\;is\;Z{\sim}X^{2}(2)\;and\;for\;Z\;to\;be\;X^{2}(1)\;is\;X{\sim}IG({\mu},\;{\mu}^{2}/{\lambda})$, where $IG({\mu},\;{\mu}^{2}/{\lambda})$ is two-parameter inverse Gaussian distribution. Also we show that X is smaller than Y in the reverse Laplace transform ratio order if and only if $X_{e}$ is smaller than $Y_{e}$ in the Laplace transform ratio order. Finally, we can get the results that if X is smaller than Y in the Laplace transform ratio order, then $Y_{L}$ is smaller than $X_{L}$ in the Laplace transform order, and that if X is smaller than Y in the reverse Laplace transform ratio order, then $_{\mu}X_{L}$ is smaller than $_{\nu}Y_{L}$ in the Laplace transform order.

• Smart Structures and Systems
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• v.1 no.2
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• pp.185-215
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• 2005

Advanced signal processing techniques have been long introduced and widely used in structural health monitoring (SHM) and nondestructive evaluation (NDE). In our research, we applied several signal processing approaches for our embedded ultrasonic structural radar (EUSR) system to obtain improved damage detection results. The EUSR algorithm was developed to detect defects within a large area of a thin-plate specimen using a piezoelectric wafer active sensor (PWAS) array. In the EUSR, the discrete wavelet transform (DWT) was first applied for signal de-noising. Secondly, after constructing the EUSR data, the short-time Fourier transform (STFT) and continuous wavelet transform (CWT) were used for the time-frequency analysis. Then the results were compared thereafter. We eventually chose continuous wavelet transform to filter out from the original signal the component with the excitation signal's frequency. Third, cross correlation method and Hilbert transform were applied to A-scan signals to extract the time of flight (TOF) of the wave packets from the crack. Finally, the Hilbert transform was again applied to the EUSR data to extract the envelopes for final inspection result visualization. The EUSR system was implemented in LabVIEW. Several laboratory experiments have been conducted and have verified that, with the advanced signal processing approaches, the EUSR has enhanced damage detection ability.

• 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 KIEE Conference
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• 1996.11a
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• pp.39-41
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• 1996

While the z-transform method is a basic mathematical tool to relate the signals only at the sampling instants in analyzing and designing sampled-data control systems, the modified z-transform which is a variation of the z-transform is widely used to represent the details of continuous signals between the sampling instants. Regarding the modified z-transform method, some properties were established to relate the modified z-transform to the regular z-transform. This paper will show that these properties, in their current forms, cause some analytic problems, when they are applied to the signals with discontinuities at the sampling instants, which accordingly limit their applications significantly. In this paper, those analytic problems will be investigated, and the theorems of the modified z-transform will be revised by adopting a new notation so that those can be correctly interpreted and used without any analytic problems in the analysis of sampled data systems. Also some useful schemes of applying the modified z-transform will be developed.

• Current Optics and Photonics
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• v.7 no.5
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• pp.529-536
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• 2023

The Morlet wavelet transform method is proposed to analyze a single interferogram with spatial carrier frequency that is captured by an optical interferometer. The method can retain low frequency components that contain the phase information of a measured optical surface, and remove high frequency disturbances by wavelet decomposition and reconstruction. The key to retrieving the phases from the low-frequency wavelet components is to extract wavelet ridges by calculating the maximum value of the wavelet transform amplitude. Afterwards, the wrapped phases can be accurately solved by multiple iterative calculations on wavelet ridges. Finally, we can reconstruct the wave-front of the measured optical element by applying two-dimensional discrete cosine transform to those wrapped phases. Morlet wavelet transform does not need to remove the spatial carrier frequency components manually in the processing of interferogram analysis, but the step is necessary in the Fourier transform algorithm. So, the Morlet wavelet simplifies the process of the analysis of interference fringe patterns compared to Fourier transform. Consequently, wavelet transform is more suitable for automated programming analysis of interference fringes and avoiding the introduction of additional errors compared with Fourier transform.