• Proceedings of the KOSOMBE Conference
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• 대한의용생체공학회 1997년도 춘계학술대회
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• pp.391-394
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• 1997

In this paper, we considered newly the use of wavelet transform in order to improve the troubles of the established methods for the analysis of ultrasound echo signals. We made the phantoms of 13.2g, 19.8g, 26.4g, 33.0g, 39.8g by ourselves, and extracted the only pulse-echo signals that reflected through the mediums using windowing technique. For determining the characterized value, the signals were wavelet transformed, absoluted, and integral calculated. As the result, we acquired characterized value of each signals, and acknowledged the differences among them except of some datas. But this will be improved by advanced work as sellecting a proper mother wavelet, a method of making phantoms, correcting the various errors, etc. We expect that wavelet transform is powerful for analysis of ultrasound signals.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제26권4B호
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• pp.471-478
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• 2001

웨이블릿 변환은 영상을 위치 정보와 주파수 정보를 가지고 표현함으로서 다른 변환 방식과는 큰 차이를 보여준다. 웨이블릿 변환된 2-D 영상은 인간의 시각 체계(Human Visual System)에 적정한 양자화 및 부호화를 위한 계층적 구조를 제공한다. 인간의 시각이 민감하게 감지하는 성분은 정확하게 부호화하고 다른 성분은 적절한 정보의 손실을 적용하는 원리를 이상적으로 적용할 수 있다. 이런 웨이블릿 변환의 통계적 특성을 이용한 제로트리(zerotree) 부호화 기법은 영상 전체에서 의미 있는 계수를 선별하여 약속된 우선 순서대로 부호화함으로써 매입파일(embedded file)을 생성한다. 본 논문에서는 Shspiro 가 제안한 EZW(embedded Zerotree wavelets) 알고리즘을 개선하여 화소 단위가 아닌 블록 단위로 부호화 함으로서 좀더 나은 성능을 가진 알고리즘을 제안하였다.

• Proceedings of the KIEE Conference
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 B
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• pp.594-596
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• 1999

It is extremely important to compress a very large multimedia data under the currently used communication networks because of the forthcoming high fast multimedia informations. Wavelets are very popular and useful mathematical tool in the field of signal processing recently. In this paper, signal compression methods using the wavelet packet transform are compared with the other compression method under same threshold condition. As the result, the compression of using the wavelet packet transform is much more effective than the other compressing methods.

• Proceedings of the KIEE Conference
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• 대한전기학회 2000년도 하계학술대회 논문집 A
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• pp.437-439
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• 2000

This paper describes a fault location technique using wavelets in underground transmission cable system Estimation of fault location is performed using data sampled at two ends of underground system. In the case of 50% fault of total underground transmission line, fault location is calculated using sampled single-end data in underground transmission line. Traveling wave is utilized in capturing the travel time of the transients along the monitored lines between the relay and the fault point. This travel time information is provided by the wavelet. Simulation was performed using EMTP. ATP Draw and MATLAB. The results of fault location shown in this paper will be evaluated as an effective suggestion for fault to location in real underground transmission line.

• Proceedings of the KSRS Conference
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.224-227
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• 2004

From 1980's, the DWT(Discrete Wavelet Transform) is applied to the data/image processing. Many people use the DWT in remote sensing for diversity purposes and they are satisfied with the wavelet theory. Though the algorithm for wavelet is very diverse, many people use the standard wavelet such as Daubechies D4 wavelet and biorthogonal 9/7 wavelet. We will overview the wavelet theory for discrete form which can be applied to the image processing. First, we will introduce the basic DWT algorithm and review the wavelet algorithm: EZW (Embedded Zerotree Wavelet), SPIHT(Set Partitioning in Hierarchical Trees), Lifting scheme, Curvelet, etc. Finally, we will suggest the properties of wavelet algorithm; and wavelet filter for each image processing in remote sensing.

• Kyungpook Mathematical Journal
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• 제55권4호
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• pp.1053-1067
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• 2015

A two-direction multiscaling function ${\phi}$ satisfies a recursion relation that uses scaled and translated versions of both itself and its reverse. This offers a more general and flexible setting than standard one-direction wavelet theory. In this paper, we investigate how to find and normalize point values and derivative values of two-direction multiscaling and multiwavelet functions. Determination of point values is based on the eigenvalue approach. Normalization is based on normalizing conditions for the continuous moments of ${\phi}$. Examples for illustrating the general theory are given.

• Smart Structures and Systems
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• 제14권3호
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• pp.445-468
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• 2014

The objective in this research is to determine the feasibility of using changes on the dynamic properties of a reinforced concrete (RC) structure to identify different levels of seismic induced damage. Damping ratio and natural frequency changes in a RC bridge column are analyzed using different signal processing techniques like Hilbert Transforms, Random Decrement and Wavelet Transforms. The data used in the analysis was recorded during a full-scale RC bridge column shake table test. The structure was subjected to ten earthquake excitations that induced different levels of inelastic demand on the column. In addition, low-intensity white noises were applied to the column in-between earthquakes. The results obtained show that the use of the damping ratio and natural frequency of vibration as damage indicators is arguable.

• Transactions on Control, Automation and Systems Engineering
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• 제2권3호
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• pp.169-174
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• 2000

In this paper, Haar wavelet-based neural network is described for the identification and control of discrete-time nonlinear dynamical systems. Wavelets are suited to depict functions with local nonlinearities and fast variations because of their intrinsic properties of finite support and self-similarity. Due to the orthonormal properties of Haar wavelet functions, wavelet neural networks result in a greatly simplified training problem. This wavelet-based scheme performs adaptively both the identification of nonlinear functions and the control of the overall system, while the multilayer neural network is applied to the control system just after its sufficient learning of the unknown functions. Simulation shows that the wavelet network can be a good alternative to a multilayer neural network with backpropagation.

• Journal of Institute of Control, Robotics and Systems
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• 제19권7호
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• pp.577-582
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• 2013

In this paper Legendre wavelets are used to approximate the solutions of linear time-invariant system. The Legendre wavelet and its integral operational matrix are presented and an efficient algorithm to solve the Sylvester matrix equation is proposed. The algorithm is based on the decomposition of the Sylvester matrix equation and the preorder traversal algorithm. Using the special structure of the Legendre wavelet's integral operational matrix, the full order Sylvester matrix equation can be solved in terms of the solutions of pure algebraic matrix equations, which reduce the computation time remarkably. Finally a numerical example is illustrated to demonstrate the validity of the proposed algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제7권5호
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• pp.1095-1100
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• 2003

The wavelet transform pair used simultaneously when two wavelets are designed to form an approximate Hilbert transform pair provide excellent property than present DWT(discrete wavelet transform), especially in field that detect wide-band signals like pulse and increase the bit rate at the same bandwidth. In this paper, the two dyadic wavelet bases which form an approximate Hilbert transform pair were designed, and flat delay filter which has the truncated coefficient vector is used in order that the two filters can form Hilbert transform relation in the process of design.