• 제목/요약/키워드: wavelet form

검색결과 85건 처리시간 0.033초

절단된 계수 벡터를 사용한 웨이브렛의 힐버트 변환쌍에 관한 연구 (A Study on Hilbert Transform Pair of Wavelet using Truncated Coefficient Vector)

  • 배상범;김남호
    • 한국정보통신학회논문지
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    • 제7권5호
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    • pp.1095-1100
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    • 2003
  • 두 개의 웨이브렛이 근사 힐버트 변환 쌍을 형성하도록 설계될 때, 동시에 사용된 웨이브렛 변환 쌍은 펄스와 같은 광대역 신호의 검출과 동일한 대역폭에서 비트 전송율을 증가시키는 분야 등에서 기존의 DWT(discrete wavelet transform)에 비해 우수한 성능을 나타낸다. 따라서, 본 논문에서는 이러한 근사 힐버트 변환 쌍을 형성하는 두 개의 dyadic 웨이브렛 기저를 설계하였으며, 설계과정에서 두 개의 필터가 힐버트 변환 관계를 형성하도록 절단된 계수 벡터를 갖는 플래트 딜레이 필터를 사용하였다.

Wavelet 변환에 의한 압축기의 이상상태 식별 (Identification of Abnormal Compressor using Wavelet Transform)

  • 정지홍;이기용;김정석;이감규
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 1995년도 추계학술대회 논문집
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    • pp.361-364
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    • 1995
  • Wavelet Transform is a new tools for signal processing, such as data compressing extraction of parameter for Reconition and Diagnostics. This transform has an advandage of a good resolution compared to Fast Fourier Transform (FFT) In this study, we employ the wavelet transform for analysis of Acoustic Emission raw signal generated form rotary compressor. In abnormal condition of rotary compressor, the state of operating condition can be classified by analizing coefficient of wavelet transformed signal.

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Wavelet Algorithms for Remote Sensing

  • CHAE Gee Ju;CHOI Kyoung Ho
    • 대한원격탐사학회:학술대회논문집
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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.

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웨이브렛을 이용한 임펄스 노이즈 검출에 관한 연구 (A Study on Detecting Impulse noise using Wavelet)

  • 배상범;김남호
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2003년도 춘계종합학술대회
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    • pp.431-434
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    • 2003
  • 신호처리 분야의 새로운 기법으로 제시된 웨이브렛 변환은 시간 및 주파수 국부성을 가지므로, 다양한 신호를 해석하는데 용이할 뿐만 아니라, 다중 해상도 해석이 가능하므로 최근 여러 분야에 응용되고 있다. 그리고, 두 개의 웨이브렛 기저가 힐버트 변환쌍을 형성하도록 설계될 때, 웨이브렛 쌍은 펄스 형태의 데이터 검출에서 기존의 DWT보다 우수한 성능을 나타낸다. 따라서, 본 연구에서는 절단된 계수 벡터에 의해 설계된 두 개의 dyadic 웨이브렛 기저를 사용하여, 임펄스 노이즈의 위치를 검출하였다.

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Representation of Wavelet Transform using a Matrix Form and Its Implementation

  • Kurosaki, Masayuki;Nishikawa, Kiyoshi;Kiya, Hitoshi
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 ITC-CSCC -1
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    • pp.282-285
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    • 2000
  • Three representations are known to implement the discrete wavelet transform (DWT) ; i.e., direct, lifting and matrix forms. In these representations, direct and lifting forms are well known so far. This paper derives the matrix form of the DWT from the direct form. Then, we implement these three representations on a programmable digital signal processor (in the following, DSP processor) and compare them in terms of the number of calculations and instruction cycles. As a result, we confirm that the lifting form has the lowest number of calculations and cycles, and the matrix form has an effective decrease in the number of cycles than other representations on the DSP processor.

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웨이블릿 신경 회로망을 이용한 자율 수중 운동체 방향 제어기 설계 (Design of Direct Adaptive Controller for Autonomous Underwater Vehicle Steering Control Using Wavelet Neural Network)

  • 서경철;박진배;최윤호
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2006년도 제37회 하계학술대회 논문집 D
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    • pp.1832-1833
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    • 2006
  • This paper presents a design method of the wavelet neural network(WNN) controller based on a direct adaptive control scheme for the intelligent control of Autonomous Underwater Vehicle(AUV) steering systems. The neural network is constructed by the wavelet orthogonal decomposition to form a wavelet neural network that can overcome nonlinearities and uncertainty. In our control method, the control signals are directly obtained by minimizing the difference between the reference track and original signal of AUV model that is controlled through a wavelet neural network. The control process is a dynamic on-line process that uses the wavelet neural network trained by gradient-descent method. Through computer simulations, we demonstrate the effectiveness of the proposed control method.

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Enhancing the Reconstruction of Acoustic Source Field Using Wavelet Transformation

  • Ko Byeongsik;Lee Seung-Yop
    • Journal of Mechanical Science and Technology
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    • 제19권8호
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    • pp.1611-1620
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    • 2005
  • This paper shows the use of wavelet transformation combined with inverse acoustics to reconstruct the surface velocity of a noise source. This approach uses the boundary element analysis based on the measured sound pressure at a set of field points, the Helmholtz integral equations and wavelet transformation for reconstructing the normal surface velocity field. The reconstructed field can be diverged due to the small measurement errors in the case of nearfield acoustic holography (NAH) using an inverse boundary element method. In order to avoid this instability in the inverse problem, the reconstruction process should include some form of regularization for enhancing the resolution of source images. The usual method of regularization has been the truncation of wave vectors associated with small singular values, although the order of an optimal truncation is difficult to determine. In this paper, a wavelet transformation is applied to reduce the computation time for inverse acoustics and to enhance the reconstructed vibration field. The computational speed-up is achieved, with solution time being reduced to $14.5\%$.

웨이블릿 신경 회로망을 이용한 이동 로봇의 경로 추종 제어 (Path Tracking Control Using a Wavelet Neural Network for Mobile Robots)

  • 오준섭;박진배;최윤호
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2003년도 하계학술대회 논문집 D
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    • pp.2414-2416
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    • 2003
  • In this raper, we present a Wavelet Neural Network(WNN) approach to the solution of the tracking problem for mobile robots that possess complexity, nonlinearity and uncertainty. The neural network is constructed by the wavelet orthogonal decomposition to form a wavelet neural network that can overcome the problems caused by local minima of optimization and various uncertainties. This network structure is helpful to determine the number of the hidden nodes and the initial value of weights with compact structure. In our control method, the control signals are directly obtained by minimizing the difference between the reference track and the pose of a mobile robot that is controlled through a wavelet neural network. The control process is a dynamic on-line process that uses the wavelet neural network trained by the gradient-descent method. Through computer simulations, we demonstrate the effectiveness and feasibility of the proposed control method.

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웨이블릿 변환영역에서 이차방정식 삽입 방법을 이용한 디지털 워터마킹 (Digital Watermarking using a Quadratic Equation Embedding Method in Wavelet Transform Domain)

  • 신용달
    • 한국멀티미디어학회논문지
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    • 제6권5호
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    • pp.870-875
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    • 2003
  • 본 논문에서는 웨이블릿 변환영역에서 비가시성을 개선하기 위하여 이차방정식 삽입방법을 이용한 디지털 워터마킹을 제안하였다. 기존의 디지털 워터마킹 방법에서 워터마크를 삽입하는 방법은 일차 방정식의 형태로 사용하였으나, 제안한 방법에서는 이차 방정식 형태로 확장하였다. 제안한 방법과 기존의 방법에 대한 성능을 평가하기 위해서 LENA, GOLDHILL, BARBARA, 및 MAN 영상을 사용하여 컴퓨터 모의실험을 행하였다. 모의실험 결과 정규화 된 유사도가 100%일 때 원 영상과 워터마크가 삽입된 영상과의 PSNR을 비교한 결과 제안한 방법이 기존의 방법들 보다 모든 영상에서 비가시성이 매우 우수함을 확인할 수 있었다.

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호모모르픽 웨이브렛 기반 MMSE 필터를 이용한 초음파영상의 스펙클 잡음 제거 (Speckle Noise Reduction for Ultrasonic Images Using Homomorphic Wavelet-based MMSE Filter)

  • 박원용;장익훈;김남철
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 제13회 신호처리 합동 학술대회 논문집
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    • pp.679-682
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    • 2000
  • In this paper, a MMSE filter in homomorphic wavelet transform domain is proposed for restoring an ultrasonic images corrupted by speckle noise. In order to remove effectively the speckle noise which is a kind of multiplicative noise, speckle noise is transformed into a form of additive noise and then the additive noise is denoised through the MMSE filter in homomorphic wavelet transform domain. The proposed method shows much higher quality in terms of ISNR and subject quality.

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