• Title/Summary/Keyword: wavelet multi-resolution analysis

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Level Selection of the Multi-Resolution Analysis(MRA) for Optimum Denoising Performance of the Discrete Wavelet Transform(DWT) (이산 웨이블릿 변환(DWT)의 디노이징 최적 성능을 위한 다해상도 분석의 레벨 선택 연구)

  • Whang, J.Y.;Kim, J.H.
    • Proceedings of the KIPE Conference
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    • 2015.07a
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    • pp.465-466
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    • 2015
  • 배터리 관리시스템(BMS;battery management system)의 중요 고려요소인 SOC(state-of-charge) 및 SOH(state-of-health)의 전기적 등가회로 모델 기반 고성능 추정의 전제 조건은 배터리 단자전압의 안정된 실험데이터 확보이다. 그러나, 예상치 않은 에러로 인해 배터리 단자전압에 노이즈 성분이 포함될 경우 SOC 및 SOH 추정알고리즘의 성능저하가 우려된다. 이를 위해, 본 논문은 이산 웨이블릿 변환(DWT;discrete wavelet transform)의 다해상도 분석(MRA;multi resolution analysis) 레벨에 따른 디노이징 최적 성능을 소개하고자 한다. 하드 임계화(hard-thresholding) 및 소프트 임계화(soft-thresholding) 기법에 따른 디노이징 성능 차이를 보이고, 각 임계화 기법 적용 시 디노이징 최적 성능을 보이는 레벨을 선택한다.

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Sliding Manifold Tuning Method Using Wavelet Neural Network (웨이브릿 신경회로망을 활용한 슬라이딩 매니폴드 조정기법)

  • 홍석우;전홍태
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2000.11a
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    • pp.195-198
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    • 2000
  • Sliding mode control method is popularly used for robustness to distrurbance and variance of systems internal parameter. However, one of the serious problem of this method is Chattering which occurs in neighborhood of sliding manifold. Another problem is that we cannot expect robustness before system starts sliding mode. A new tuning method of sliding manifold which changes the parameter of sliding manifold dynamically using Wavelet Neural Network is proposed in this paper. We can expect the better performance in sliding mode control by the wavelet neural networks excellent property of approximating arbitrary function for multi-resolution analysis and decrease chattering drastically.

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A wavelet-based fast motion estimation (웨이블릿 기반의 고속 움직임 예측 기법)

  • 배진우;선동우;유지상
    • Journal of Broadcast Engineering
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    • v.8 no.3
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    • pp.297-305
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    • 2003
  • In this paper, we propose a wavelet based fast motion estimation algorithm for video sequence encoding with very low bit-rate. By using one of properties oi wavelet transform, multi-resolution analysis(MRA) property and spatial Interpolation of an image, we are able to reduce both prediction error and computational complexity at the same time. Especially, by defining a significant block(SB) based on the differential information of wavelet coefficients between successive frames, the proposed algorithm makes up a defect of multi-resolution motion estimation(MRME) algorithm of increasing the number of motion vectors. As experimental results. we can reduce the computational load up to 70% but also improve PSNR up to about 0.1 ∼ 1.2 dB comparing with the MRME algorithm.

A Defect Inspection Algorithm Using Multi-Resolution Analysis based on Wavelet Transform (웨이블릿 다해상도 분석에 의한 디지털 이미지 결점 검출 알고리즘)

  • Kim, Kyung-Joon;Lee, Chang-Hwan;Kim, Joo-Yong
    • Textile Coloration and Finishing
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    • v.21 no.1
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    • pp.53-58
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    • 2009
  • A real-time inspection system has been developed by combining CCD based image processing algorithm and a standard lighting equipment. The system was tested for defective fabrics showing nozzle contact scratch marks, which were one of the frequently occurring defects. Multi-resolution analysis(MRA) algorithm were used and evaluated according to both their processing time and detection rate. Standard value for defective inspection was the mean of the non-defect image feature. Similarity was decided via comparing standard value with sample image feature value. Totally, we achieved defective inspection accuracy above 95%.

Image Processing Considering Directional Extraction by Multi-Resolution Signal Analysis. (다해상도 신호분석에 의한 방향성 추출을 통한 영상처리)

  • Jeon, Woo-Sang;Kim, Young-Gil;Han, Kun-Hee
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.10
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    • pp.3928-3934
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    • 2010
  • To restore image degraded by motion blur and additive noise, In conventional method, regularization is usually applied to all over the image without considering the local characteristics of image. As a result, ringing artifacts appear in edge regions and the noise amplification is introduced in flat regions. To solve this problem we propose an adaptive regularization iterative restoration using wavelet directional considering edges and the regularization operator with no direction for flat regions. We verified that the proposed method showed results in the suppression of the noise amplification in flat regions, and introduced less ringing artifacts in edge regions.

Adaptive Wavelet-Galerkin Method for Structural Ananlysis (구조해석을 위한 적응 웨이블렛-캘러킨 기법)

  • Kim, Yun-Yeong;Jang, Gang-Won
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.24 no.8 s.179
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    • pp.2091-2099
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    • 2000
  • The object of the present study is to present an adaptive wavelet-Galerkin method for the analysis of thin-walled box beam. Due to good localization properties of wavelets, wavelet methods emerge as alternative efficient solution methods to finite element methods. Most structural applications of wavelets thus far are limited in fixed-scale, non-adaptive frameworks, but this is not an appropriate use of wavelets. On the other hand, the present work appears the first attempt of an adaptive wavelet-based Galerkin method in structural problems. To handle boundary conditions, a fictitous domain method with penalty terms is employed. The limitation of the fictitious domain method is also addressed.

Application of the Wavelet transformation to denoising and analyzing the speech

  • Hung Phan Duy;Lan Huong Nguyen Thi;Ngoc Yen Pham Thi;Castelli Eric
    • Proceedings of the IEEK Conference
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    • summer
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    • pp.249-253
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    • 2004
  • Wavelet transform (WT) has attracted most engineers and scientists because of its excellent properties. The coherence of practical approach and a theoretical basis not only solves currently important problems, but also gives the potential of formulating and solving completely new problems. It has been show that multi-resolution analysis of Wavelet transforms is good solution in speech analysis and threshold of wavelet coefficients has near optimal noise reduction property for many classes of signals. This paper proposed applications of wavelet in speech processing: pitch detection, voice-unvoice (V -UV) decision, denoising with the detailed algorithms and results.

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Wavelet analysis and enhanced damage indicators

  • Lakshmanan, N.;Raghuprasad, B.K.;Muthumani, K.;Gopalakrishnan, N.;Basu, D.
    • Smart Structures and Systems
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    • v.3 no.1
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    • pp.23-49
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    • 2007
  • Wavelet transforms are the emerging signal-processing tools for damage identification and time-frequency localization. A small perturbation in a static or dynamic displacement profile could be captured using multi-resolution technique of wavelet analysis. The paper presents the wavelet analysis of damaged linear structural elements using DB4 or BIOR6.8 family of wavelets. Starting with a localized reduction of EI at the mid-span of a simply supported beam, damage modeling is done for a typical steel and reinforced concrete beam element. Rotation and curvature mode shapes are found to be the improved indicators of damage and when these are coupled with wavelet analysis, a clear picture of damage singularity emerges. In the steel beam, the damage is modeled as a rotational spring and for an RC section, moment curvature relationship is used to compute the effective EI. Wavelet analysis is performed for these damage models for displacement, rotation and curvature mode shapes as well as static deformation profiles. It is shown that all the damage indicators like displacement, slope and curvature are magnified under higher modes. A localization scheme with arbitrary location of curvature nodes within a pseudo span is developed for steady state dynamic loads, such that curvature response and damages are maximized and the scheme is numerically tested and proved.

Gamma spectrum denoising method based on improved wavelet threshold

  • Xie, Bo;Xiong, Zhangqiang;Wang, Zhijian;Zhang, Lijiao;Zhang, Dazhou;Li, Fusheng
    • Nuclear Engineering and Technology
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    • v.52 no.8
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    • pp.1771-1776
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    • 2020
  • Adverse effects in the measured gamma spectrum caused by radioactive statistical fluctuations, gamma ray scattering, and electronic noise can be reduced by energy spectrum denoising. Wavelet threshold denoising can be used to perform multi-scale and multi-resolution analysis on noisy signals with small root mean square errors and high signal-to-noise ratios. However, in traditional wavelet threshold denoising methods, there are signal oscillations in hard threshold denoising and constant deviations in soft threshold denoising. An improved wavelet threshold calculation method and threshold processing function are proposed in this paper. The improved threshold calculation method takes into account the influence of the number of wavelet decomposition layers and reduces the deviation caused by the inaccuracy of the threshold. The improved threshold processing function can be continuously guided, which solves the discontinuity of the traditional hard threshold function, avoids the constant deviation caused by the traditional soft threshold method. The examples show that the proposed method can accurately denoise and preserves the characteristic signals well in the gamma energy spectrum.

Droplet Geometry and Its Volume Analysis (기름방울 형상 및 그 체적 분석법)

  • Yoon, Moon-Chul
    • Tribology and Lubricants
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    • v.24 no.6
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    • pp.320-325
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    • 2008
  • The recent industrial application requires technical methods to get the cutting fluid droplet surfaces in particular from the viewpoint of topography and micro texture. To characterize the surface topography of droplet, the combination of the confocal laser scanning microscope (CLSM) and wavelet filtering is well suited for obtaining the droplet geometry encountered in tribological research. This technique indicates a better agreement in obtaining an appropriate droplet surface obtained by the CLSM over a detail range of surface accuracy (resolution: $2{\mu}m$). And the results allow an excellent accuracy in a measurement of a droplet surface. The combination of extended focal depth measurement configured and multi-scale wavelet filtering has proven that it can construct a droplet surface in a successive and accurate way. A multi-scale approach of wavelet filtering was developed based on the decomposition and reconstruction of droplet surface by 2D wavelet transform using db9 (a mother wavelet of daubechies). Also this technique can be extended to characterize the quantification of droplet properties and other field in a wide range of scales. Finally this method is verified to be a better droplet surface modeling in a micro scale arising in a mist machining.