• 제목/요약/키워드: Wavelet basis

검색결과 143건 처리시간 0.026초

웨이블릿 변환을 이용한 누전점 검출에 관한 연구 (A Study on the Method for Detecting of Leakage Point using Wavelet Transforms)

  • 박건우;김일권;김진수;김광순;김영일
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2008년도 제39회 하계학술대회
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    • pp.173-174
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    • 2008
  • Wavelet transform is a new method for power system analysis. On the basis of extensive investigation, optimal mother wavelets for the detection of leakage current are chosen. The recommended mother wavelet is 'Daubechies 4' wavelet. This paper proposes a technique for modeling toe finding point of leakage current in distribution system using wavelet transform and EMTP MODELS.

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Adaptive Wavelet Based Speech Enhancement with Robust VAD in Non-stationary Noise Environment

  • Sungwook Chang;Sungil Jung;Younghun Kwon;Yang, Sung-il
    • The Journal of the Acoustical Society of Korea
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    • 제22권4E호
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    • pp.161-166
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    • 2003
  • We present an adaptive wavelet packet based speech enhancement method with robust voice activity detection (VAD) in non-stationary noise environment. The proposed method can be divided into two main procedures. The first procedure is a VAD with adaptive wavelet packet transform. And the other is a speech enhancement procedure based on the proposed VAD method. The proposed VAD method shows remarkable performance even in low SNRs and non-stationary noise environment. And subjective evaluation shows that the performance of the proposed speech enhancement method with wavelet bases is better than that with Fourier basis.

Application of the Wavelet transformation to denoising and analyzing the speech

  • Hung Phan Duy;Lan Huong Nguyen Thi;Ngoc Yen Pham Thi;Castelli Eric
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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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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웨이블릿변환에 기반한 정보압축 (Information Compression Based on Wavelet Transform)

  • 김응규;이수종
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2006년도 하계종합학술대회
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    • pp.333-334
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    • 2006
  • In this study, information compression based on the wavelet technique is described. The principle of signal or image compression is performed by optimization of quantization, that is the bit allocation taking advantage of their energy concentration in low frequency components. The wavelet transform is one of frequency decomposition, such as the discrete cosine transform or sub-band filtering, and it is also implemented as a filter bank. Wavelet transform with use of spatially localized basis function can reduce several drawbacks in conventional methods. The benifit of wavelet based compression method is described as comparing the transform method to another ones.

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Riesz and Tight Wavelet Frame Sets in Locally Compact Abelian Groups

  • Sinha, Arvind Kumar;Sahoo, Radhakrushna
    • Kyungpook Mathematical Journal
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    • 제61권2호
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    • pp.371-381
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    • 2021
  • In this paper, we attempt to obtain sufficient conditions for the existence of tight wavelet frame sets in locally compact abelian groups. The condition is generated by modulating a collection of characteristic functions that correspond to a generalized shift-invariant system via the Fourier transform. We present two approaches (for stationary and non-stationary wavelets) to construct the scaling function for L2(G) and, using the scaling function, we construct an orthonormal wavelet basis for L2(G). We propose an open problem related to the extension principle for Riesz wavelets in locally compact abelian groups.

Accurate Segmentation Algorithm of Video Dynamic Background Image Based on Improved Wavelet Transform

  • Ming, Ming
    • Journal of Information Processing Systems
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    • 제18권5호
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    • pp.711-718
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    • 2022
  • In this paper, an accurate segmentation algorithm of video dynamic background image (VDBI) based on improved wavelet transform is proposed. Based on the smooth processing of VDBI, the traditional wavelet transform process is improved, and the two-layer decomposition of dynamic image is realized by using two-dimensional wavelet transform. On the basis of decomposition results and information enhancement processing, image features are detected, feature points are extracted, and quantum ant colony algorithm is adopted to complete accurate segmentation of the image. The maximum SNR of the output results of the proposed algorithm can reach 73.67 dB, the maximum time of the segmentation process is only 7 seconds, the segmentation accuracy shows a trend of decreasing first and then increasing, and the global maximum value can reach 97%, indicating that the proposed algorithm effectively achieves the design expectation.

Wavelet-based automatic identification method of axle distribution information

  • Wang, Ning-Bo;Ren, Wei-Xin;Chen, Zhi-Wei
    • Structural Engineering and Mechanics
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    • 제63권6호
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    • pp.761-769
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    • 2017
  • Accurately extracting the axle distribution information of a passing vehicle from bridge dynamic responses experiences a key and challenging step in non-pavement bridge weigh-in-motion (BWIM). In this article, the wavelet transformation is adopted and the wavelet coefficient curve is used as a substitute for dynamic response. The driving frequency is introduced and expanded to multi-axle vehicle, and the wavelet coefficient curve on specific scale corresponding to the driving frequency is confirmed to contain obvious axle information. On this basis, an automatic method for axle distribution information identification is proposed. The specific wavelet scale can be obtained through iterative computing, and the false peaks due to bridge vibration can be eliminated through cross-correlation analysis of the wavelet coefficients of two measure points. The integrand function that corresponds to the maximum value of the cross-correlation function is used to identify the peaks caused by axles. A numerical application of the proposed axle information identification method is carried out. Numerical results demonstrate that this method acquires precise axle information from the responses of an axle-insensitive structure (e.g., girder) and decreases the requirement of sensitivity structure of BWIM. Finally, an experimental study on a full-scale simply supported bridge is also conducted to verify the effectiveness of this method.

유전 알고리즘을 이용한 모듈라 웨이블릿 신경망의 최적 구조 설계 (Optimal Structure of Modular Wavelet Network Using Genetic Algorithm)

  • 서재용;조현찬;김용택;전홍태
    • 전자공학회논문지SC
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    • 제38권5호
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    • pp.7-13
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    • 2001
  • 단일 신경망에 기반한 웨이블릿 이론과 모듈라 개념을 결합하여 기존의 웨이블릿 신경망이나 모듈라 네트워크의 일종인 모듈라 웨이블릿 신경망이 제안되었다. 본 논문에서는 유전 알고리즘을 사용하여 모듈라 웨이블릿 신경망의 최적구조를 효과적으로 설계하는 방법을 제시하였다. 각 모듈을 구성하는 웨이블릿 신경망의 웨이블릿 기저함수의 팽창과 이동계수를 결장하기 위해 유전 알고리즘을 사용하였다. 제안한 최적 구조 설계 알고리즘을 근사화 문제에 적용하여 우수성을 검증하였다.

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이동 로봇의 경로 추종을 위한 웨이블릿 퍼지 신경 회로망 기반 직접 적응 제어 시스템 (Direct Adaptive Control System for Path Tracking of Mobile Robot Based on Wavelet Fuzzy Neural Network)

  • 오준섭;박진배;최윤호
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2004년도 하계학술대회 논문집 D
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    • pp.2432-2434
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    • 2004
  • In this paper, we present a novel approach for the structure of Fuzzy Neural Network(FNN) based on wavelet function and apply this network structure to the solution of the tracking problem for mobile robots. Generally, the wavelet fuzzy model(WFM) has the advantage of the wavelet transform by constituting fuzzy basis function(FBF) and the conclusion part to equalize the linear combination of FBF with the linear combination of wavelet functions. However, it is very difficult to identify the fuzzy rules and to tune the membership functions of the fuzzy reasoning mechanism. Neural networks, on the other hand, utilize their learning capability for automatic identification and tuning. Therefore, we design a wavelet based FNN structure(WFNN) that merges these advantages of neural network, fuzzy model and wavelet. To verify the efficiency of our network structure, we evaluate the tracking performance for mobile robot and compare it with those of the FNN and the WFM.

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1-패스 공간 적응적 웨이블릿 임계화를 사용한 영상의 노이즈제거 (1-PASS SPATIALLY ADAPTIVE WAVELET THRESHOLDING FOR IMAGE DENOSING)

  • 백승수
    • 한국컴퓨터정보학회논문지
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    • 제8권4호
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    • pp.7-12
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    • 2003
  • 본 연구는 이미지 디노이징을 위한 1-패스 공간 적응적 웨이블릿 임계화를 제안하였다. 웨이블릿 임계화를 이용한 디노이징은 최상의 기저함수와 임계치를 구하는 연구에 집중되어왔으나 이미지의 통계적 특성의 변화에 효과적으로 적용되는 방법은 아직 충분하지 않은 상태이다. 제안된 방법에 Overcomplete wavelet expansion을 사용하여 노이즈의 제거에 좋은 결과를 나타내었다. 그리고 실험 결과는 Wiener 필터링 방법과 Level dependent 임계치, 2-패스 공간적응적 웨이블릿 임계화 방법보다 좋은 결과를 나타내었다.

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