• Journal of Korea Multimedia Society
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• v.3 no.5
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• pp.461-469
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• 2000

A wavelet analysis in a field of analytics is to create a reconstruction theorem of Plancherel form. And a series of wavelet is to create a discrete is to create a discrete reconstruction theorem for a frame theory and a multiresolution analysis theory. As a generation of reconstruction theorem, a wavelet correspond to it is generated. That is to be like a basic wavelet which is satisfied an admissibility condition in CWT and a Daubechies wavelet using MRA in wavelet series and a Meyer wavelet using a frame theory. In this paper, we discover a discrete reconstruction theorem which is superior to a conventional discrete reconstruction theorem by extending admissibility condition used in CWT and develop a New $L^1$-wavelet group. A new $L^1$-wavelet is applied to a signal reconstruction and a signal analysis in time-frequency region.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.341-343
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• 2005

This paper introduces a compression algorithm for power quality disturbance signal via the discrete wavelet transform, DWT. Algorithm to estimate a time delay from the power quality disturbance signal is proposed. Pseudo-stationary signal is constructed from the estimated time delay. A difference signal or nonstationary signal is obtained by removing a pseudo-stationary signal from a disturbance signal. DWT is applied to a difference signal. The threshold is applied to reduce a number of coefficients. Simulation results show the resonable compression ratio while keep low signal distortion.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1185-1192
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• 2015

In this paper, a study of advanced sound source localization is conducted by eliminating the noise of the sound source using the discrete wavelet transform. And experiments are conducted to evaluate the performance of the proposed system that the mobile robot follows sound source stably. In addition, we compare the position estimation performance by applying a discrete wavelet transform to improve the reliability of the sound signal. The experimental results reveal that the de-nosing filter which removes the noise component in sound source can make the performance of position estimation more precisely and help the mobile robot distinguish the objective sound source clearly.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.3
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• pp.363-368
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• 2008

In this paper, the Resistive Companion Form(RCF) analysis method is applied to analyze small signal stability of power systems including thyristor controlled FACTS equipments such as SVC. The eigenvalue sensitivity analysis algorithm in discrete systems based on the RCF analysis method is presented and applied to the power system including SVC. As a result of simulation, the RCF analysis method is proved very effective to precisely calculate the variations of eigenvalues or newly generated unstable oscillation modes after periodic switching operations of SVC. Also the eigenvalue sensitivity analysis method based on the RCF analysis method enabled to precisely calculate eigenvalue sensitivity coefficients of controller parameters about the dominant oscillation mode after periodic switching operations in discrete systems. These simulation results are different from those of the conventional continuous system analysis method such as the state space equation and proved that the RCF analysis method is very effective to analyze the discrete power systems including periodically operated switching equipments such as SVC.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2001.10a
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• pp.169-173
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• 2001

This study presents the results of decoupling of free decay roll test data by discrete wavelet transform. Free roll decay test was performed to decide the coefficients of damping terms in equation of motion. During the experiment, a slight yaw motion was found while the model was in the free roll decay motion. Discrete wavelet transform was applied to the signal to extract the pure roll motion. The results were compared to those of the Fourier transform. DWT was able to decouple the two signals efficiently while the Fourier transform was not.

• Journal of Korean Society for Quality Management
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• v.27 no.2
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• pp.101-111
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• 1999

The purpose of Taguchi's robust design lies in quality improvement by making the performance of a system robust against noise. Robust design with continuous performance characteristics has been the subject of much interest. However relatively little work has been done for discrete characteristics such as 0-1, good-medium-bad, etc. This paper is concerned with robust design of a discrete dynamic system. We first investigate the Taguchi method for robust design with discrete dynamic characteristics and discuss his standard error probability (SEP). Then we propose a generalized SEP, which makes it possible to encompass a wider class of robust design problems. An illustration is also given by example.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.14-16
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• 1988

With the development of VLSI technology, research on special processors for high-speed processing is on the increase and studies are focused on designing VLSI-oriented processors for signal processing. This paper processes a one-dimensional systolic array for Discrete Hartley Transform implementation and also processes processing element which is well described for algorithm. The discrete Hartley Transform(DHT) is a real-valued transform closely related to the DFT of a real-valued sequence can be exploited to reduce both the storage and the computation requried to produce the transform of real-valued sequence to a real-valued spectrum while preserving some of the useful properties of the DFT is something preferred. Finally, the architecture of one-dimensional 8-point systolic array, the detailed diagram of PE, total time units concept on implementation this arrays, and modularity are described.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.487-492
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• 2004

This paper deals with modeling method and application of Fuzzy Discrete Event System(FDES). FDES have characteristics which Crisp Discrete Event System(CDES) can't deals with and is constituted with the events that is determined by vague and uncertain judgement like biomedical or traffic control. In general, the modeling method of CDES has been studied many times, but that of FDES hasn't been nearly studied by qualitative character and scarcity of applicated system. This paper models traffic system with FDES's character in FTTPN and designs a traffic signal controller.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.3
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• pp.133-145
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• 2012

This paper describes the high density discrete wavelet transformation which is one that expands an N point signal to M transform coefficients with M > N. The double-density discrete wavelet transform is one of the high density discrete wavelet transformation. This transformation employs one scaling function and two distinct wavelets, which are designed to be offset from one another by one half. And it is nearly shift-invariant. Similarly, triple-density discrete wavelet transformation is a new set of dyadic wavelet transformation with two generators. The construction provides a higher sampling in both time and frequency. Specifically, the spectrum of the first wavelet is concentrated halfway between the spectrum of the second wavelet and the spectrum of its dilated version. In addition, the second wavelet is translated by half-integers rather than whole-integers in the frame construction. This arrangement leads to high density wavelet transformation. But this new transform is approximately shift-invariant and has intermediate scales. In two dimensions, this transform outperforms the standard and double-density discrete wavelet transformation in terms of multiple directions. Resultingly, the proposed wavelet transformation services good performance in image and video processing fields.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1068-1081
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• 2019

Signal complexity is one point of view to analyze the biological signal. It arises as a result of the physiological signal produced by biological systems. Signal complexity can be used as a method in extracting the feature for a biological signal to differentiate a pathological signal from a normal signal. In this research, Hjorth descriptors, one of the signal complexity measurement techniques, were measured on signal sub-band as the features for lung sounds classification. Lung sound signal was decomposed using two wavelet analyses: discrete wavelet transform (DWT) and wavelet packet decomposition (WPD). Meanwhile, multi-layer perceptron and N-fold cross-validation were used in the classification stage. Using DWT, the highest accuracy was obtained at 97.98%, while using WPD, the highest one was found at 98.99%. This result was found better than the multi-scale Hjorth descriptor as in previous studies.