• Title/Summary/Keyword: Daubechies transform

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The FPGA Implementation of Wavelet Transform Chip using Daubechies′4 Tap Filter for DSP Application

  • Jeong, Chang-Soo;Kim, Nam-Young
    • Proceedings of the IEEK Conference
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    • 1999.11a
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    • pp.376-379
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    • 1999
  • The wavelet transform chip is implemented with Daubechies' 4 tap filter. It works at 20MHz in Field Programmable Gate array (FPGA) implementation of Quadrature Mirror Filter(QMF) Lattice Structure. In this paper, the structure contains taro-channel quadrature mirror filter, data format converter(DFC), delay control unit(DCU), and three 20$\times$8 bits real multiplier. The structures for the DFC and DCU need to he regular and scalable, require minimum number of regular, and thereby lead to an efficient and scalable architecture for the Discrete Wavelet Transform(DWT). These results present the possibility that it can be used in Digital Signal Processing(DSP) application faster than Fourier transform at small area with lour cost.

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Internal Fault Detection and Fault Type Discrimination for AC Generator Using Detail Coefficient Ratio of Daubechies Wavelet Transform (다우비시 웨이브릿 변환의 상세계수 비율을 이용한 교류발전기의 내부고장 검출 및 고장종류 판별)

  • Park, Chul-Won;Shin, Kwang-Chul;Shin, Myong-Chul
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.58 no.2
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    • pp.136-141
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    • 2009
  • An AC generator is an important components in producing a electric power and so it requires highly reliable protection relays to minimize the possibility of demage occurring under fault conditions. Conventionally, a DFT based RDR has been used for protecting the generator stator winding. However, when DFTs based on Fourier analysis are used, it has been pointed out that defects can occur during the process of transforming a time domain signal into a frequency domain one which can lead to loss of time domain information. This paper proposes the internal fault detection and fault type discrimination for the stator winding by applying the detailed coefficients by Daubechies Wavelet Transform to overcome the defects in the DFT process. For the case studies reported in the paper, a model system was established for the simulations utilizing the ATP, and this verified the effectiveness of the proposed technique through various off-line tests carried out on the collected data. The propose method is shown to be able to rapidly identify internal fault and did not operate a miss-operation for all the external fault tested.

The Detection of Voltage Sag using Wavelet Transform (웨이브렛 변환을 이용한 Voltage Sag 검출)

  • Kim, Cheol-Hwan;Go, Yeong-Hun
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.49 no.9
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    • pp.425-432
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    • 2000
  • Wavelet transform is a new method fro electric power quality analysis. Several types of mother wavelets are compared using voltage sag data. Investigations on the use of some mother wavelets, namely Daubechies, Symlets, Coiflets, Biorthogonal, are carried out. On the basis of extensive investigations, optimal mother wavelets for the detection of voltage sag are chosen. The recommended mother wavelet is 'Daubechies 4(db4)' wavelet. 'db4', the most commonly applied mother wavelet in the power quality analysis, can be used most properly in disturbance phenomena which occurs rapidly for a short time. This paper presents a discrete wavelet transform approach for determining the beginning time and end time of voltage sags. The technique is based on utilising the maximum value of d1(at scale 1) coefficients in multiresolution analysis(MRA) based on the discrete wavelet transform. The procedure is fully described, and the results are compared with other methods for determining voltage sag duration, such as the RMS voltage and STFT(Short-Time Fourier Transform) methods. As a result, the voltage sag detection using wavelet transform appears to be a reliable method for detecting and measuring voltage sags in power quality disturbance analysis.

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An Efficient VLSI Architecture for the Discrete Wavelet Transform (이산 웨이브렛 변환을 위한 효율적인 VLSI 구조)

  • Pan, Sung-Bum;Park, Rae-Hong
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.6
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    • pp.96-103
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    • 1999
  • This paper proposes efficient VLSI architecture for computation of the 1-D discrete wavelet transform (DWT). The proposed VLSI architecture computes the wavelet lowpass and highpass output sequences using the product term anhm, $n,m{\ge}0$, where an and hm denote the imput sequence and the wavelet lowpass filter coefficient, respectively. Whereas the conventional architectures compute the lowpass and highpass output sequences using the product terms anhm and angm, respectively, where gm denotes the wavelet highpass filter coefficient. The proposed architecture is applied to computation of the Daubechies 4-tap wavelet transform using the relationships between the Daubechies wavelet filter coefficients. Performance comparison of various architectures for computation of the 1-D DWT are presented. Note that the proposed architecture does not require extra processing units whereas the conventional architectures need them. Also it is modeled in very high speed integrated circuit hardware description language (VHDL) and simulated to show its functional validity.

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Noise Suppression of NMR Spectrum by Shifted Harr Wavelet Transform

  • Hoshik Won;Kim, Daesung
    • Journal of the Korean Magnetic Resonance Society
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    • v.5 no.2
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    • pp.66-72
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    • 2001
  • The noise suppression of time domain NMR data by discrete wavelet transform with high order Daubechies wavelet coefficients exhibits severe peak distortion and incomplete noise suppression near real signal. However, the fact that even a shift averaged Harr wavelet transform with a set of Daubechies wavelet coefficients (1/2, -l/2) can be used as a new and excellent tool to distinguish real peaks from the noise contaminated NMR signal is introduced. New algorithms of shift averaged Harr wavelet were developed and quantitatively evaluated in terms of threshold and signal to noise ratio (SNR).

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A Study on the EMI Signal Analysis and Denoising Using a Wavelet Transform (웨이브렛 변환을 이용한 EMI 신호해석 및 잡음제거에 관한 연구)

  • 윤기방;박제헌;김기두
    • Journal of the Korean Institute of Telematics and Electronics T
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    • v.35T no.3
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    • pp.37-45
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    • 1998
  • In this paper, the different frequency component and time informations from an EMI signal are extracted simultaneously using a wavelet transform and the results of transform in the time and frequency domain are analyzed. Frequencies are extracted from the EMI signal by performing the multiresolution analysis using the Daubechies-4 filter coefficients and the time information through the results of wavelet transform. We have tried the correlation analysis to evaluate the results of wavelet transform. We have chosen the optimal wavelet function for an object signal by comparing the transformed results of various wavelet functions and verified the simulation examples of waveform and harmonic analysis using a wavelet transform. We have proved the denoising effect to the EMI signal using the soft thresholding technique.

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Volumetric Data Encoding Using Daubechies Wavelet Filter (Daubechies 웨이블릿 필터를 사용한 볼륨 데이터 인코딩)

  • Hur, Young-Ju;Park, Sang-Hun
    • The KIPS Transactions:PartA
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    • v.13A no.7 s.104
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    • pp.639-646
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    • 2006
  • Data compression technologies enable us to store and transfer large amount of data efficiently, and become more and more important due to increasing data size and the network traffic. Moreover, as a result of the increase of computing power, volumetric data produced from various applied science and engineering fields has been getting much larger. In this Paper, we present a volume compression scheme which exploits Daubeches wavelet transform. The proposed scheme basically supports lossy compression for 3D volume data, and provides unit-wise random accessibility. Since our scheme shows far lower error rates than the previous compression methods based on Haar filter, it could be used well for interactive visualization applications as well as large volume data compression requiring image fidelity.

Character Extraction Using Wavelet Transform and Fuzzy Clustering (웨이브렛 변환과 퍼지 군집화를 활용한 문자추출)

  • Hwang, Jung-Won;Hwang, Jae-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.4 s.316
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    • pp.93-100
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    • 2007
  • In this paper, a novel approach based on wavelet transform is proposed to process the scraped character which is represented on digital image. The basis idea is that the scraped character is described by its textured neighborhood, and it is decomposed into multiresolution features at different levels with its background region. The image is first decomposed into sub bands by applying Daubechies wavelets. Character features are extracted from the low frequency sub-bands by partition, FCM clustering and area-based region process. High frequency ones are activated by applying local energy density over a moving mask. Features are synthesized in order to reconstruct the original image state through inverse wavelet transform Background region is eliminated and character is extracted. The experimental results demonstrate the effectiveness of the proposed method.

Application of Wavelet Transform for Fault Discriminant of Generator (발전기의 고장 판별을 위한 웨이브릿 변환의 적용)

  • Park, Chul-Won
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.64 no.1
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    • pp.35-40
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    • 2015
  • Generators are the most complex and expensive single element in a power system. The generator protection relays should to minimize damage during fault states and must be designed for maximum reliability. A conventional CDR(Current Differential Relaying) technique based on DFT(Discrete Fourier Transform) filter have the disadvantages that the time information can lead to loss in the process of converting the signal from the time domain to the frequency domain. A WT(Wavelet transform) and WT analysis is known that it is possible with the local analysis of the fault and transient signal. In this paper, to overcome the defects in the DFT process, an application of WT for fault detection of generator is presented. This paper describes an selection of mother Wavelet to detect faults of generator. Using collected data from the fault simulation with ATPdraw, we analyzed the several mother Wavelet through the course of MLD(multi-level decomposition) using MATLAB software. Finally, it can be seen that the proposed technique using detail coefficient of Daubechies level 2 which can be fault discriminant of generator.

A Design of Parallel Processing for Wavelet Transformation on FPGA (ICCAS 2005)

  • Ngowsuwan, Krairuek;Chisobhuk, Orachat;Vongchumyen, Charoen
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.864-867
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    • 2005
  • In this paper we introduce a design of parallel architecture for wavelet transformation on FPGA. We implement wavelet transforms though lifting scheme and apply Daubechies4 transform equations. This technique has an advantage that we can obtain perfect reconstruction of the data. We divide our process to high pass filter and low pass filter. With this division, we can find coefficients from low and high pass filters simultaneously using parallel processing properties of FPGA to reduce processing time. From the equations, we have to design real number computation module, referred to IEEE754 standard. We choose 32 bit computation that is fine enough to reconstruct data. After that we arrange the real number module according to Daubechies4 transform though lifting scheme.

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