• 제목/요약/키워드: Wavelet basis functions

검색결과 37건 처리시간 0.026초

웨이블릿 변환을 이용한 시간 지연 추정법 (Time Delay Estimation using Wavelet Transform)

  • 김도형;박영진
    • 한국음향학회:학술대회논문집
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    • 한국음향학회 2000년도 하계학술발표대회 논문집 제19권 1호
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    • pp.165-168
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    • 2000
  • A fast estimation method using wavelet transform for a time delay system is proposed. Main point of this method is to get the wavelet transform of the correlation between the input signal and delayed signal using transformed signals. But wavelet transform using Haar wavelet functions has basis with different phases and can offers a bisection method to estimate a time delay of a signal. Selective computation of the transform of correlation is performed and the computational complexity is reduced. Computational order of this method is O(N log N) and it is much love. than a simple correlation esimation when the length of signal is long.

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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.

AR 모델에 의한 중복 웨이브렛 변환의 성능 평가 (Performance Evaluation of Overlapping wavelet Transform for AR Model)

  • 권상근;김재균
    • 전자공학회논문지B
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    • 제30B권1호
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    • pp.56-62
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    • 1993
  • OWT is a tool for block transform coding with wavelet basis functions that overlap adjacent blocks. The OWT can reduce the block effect. In this paper performances of OWT are evaluated for AR model. Some simulation results show that performances are nearly same to DCT, but block effect is reduced to very low level.

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중복 웨이브렛 변환 (Overlapping Wavelet Transform)

  • 권상근
    • 한국통신학회논문지
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    • 제17권6호
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    • pp.604-612
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    • 1992
  • 본 논문에서는 인접 블록을 중복하며 변환하는 방식이 제안되었다. 제안된 방식은 웨이브렛 기저를 가지며 이러한 변환은 블록 효과를 감소시킨다. 모의실험 결과 중복 웨이브렛 변환은 이산 여현 변환과 거의 같은 성능을 보이며 블록 효과는 많이 감소함을 알 수 있었다.

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Protection Assessment using Reduced Power System Fault Data

  • Littler, T.B.
    • Journal of Electrical Engineering and Technology
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    • 제2권2호
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    • pp.172-177
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    • 2007
  • Wavelet transforms provide basis functions for time-frequency analysis and have properties that are particularly useful for the compression of analogue point on wave transient and disturbance power system signals. This paper evaluates the compression properties of the discrete wavelet transform using actual power system data. The results presented in the paper indicate that reduction ratios up to 10:1 with acceptable distortion are achievable. The paper discusses the application of the reduction method for expedient fault analysis and protection assessment.

WAVELET-BASED FOREST AREAS CLASSIFICATION BY USING HIGH RESOLUTION IMAGERY

  • Yoon Bo-Yeol;Kim Choen
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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    • pp.698-701
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    • 2005
  • This paper examines that is extracted certain information in forest areas within high resolution imagery based on wavelet transformation. First of all, study areas are selected one more species distributed spots refer to forest type map. Next, study area is cut 256 x 256 pixels size because of image processing problem in large volume data. Prior to wavelet transformation, five texture parameters (contrast, dissimilarity, entropy, homogeneity, Angular Second Moment (ASM≫ calculated by using Gray Level Co-occurrence Matrix (GLCM). Five texture images are set that shifting window size is 3x3, distance .is 1 pixel, and angle is 45 degrees used. Wavelet function is selected Daubechies 4 wavelet basis functions. Result is summarized 3 points; First, Wavelet transformation images derived from contrast, dissimilarity (texture parameters) have on effect on edge elements detection and will have probability used forest road detection. Second, Wavelet fusion images derived from texture parameters and original image can apply to forest area classification because of clustering in Homogeneous forest type structure. Third, for grading evaluation in forest fire damaged area, if data fusion of established classification method, GLCM texture extraction concept and wavelet transformation technique effectively applied forest areas (also other areas), will obtain high accuracy result.

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멀티스케일 적응 웨이블렛-갤러킨 기법을 이용한 박막 고유치 문제 해석 (Eigenvalue Analysis of a Membrane Using the Multiscale Adaptive Wavelet-Galerkin Method)

  • 이용섭;김윤영
    • 대한기계학회논문집A
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    • 제28권3호
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    • pp.251-258
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    • 2004
  • Since the multiscale wavelet-based numerical methods allow effective adaptive analysis, they have become new analysis tools. However, the main applications of these methods have been mainly on elliptic problems, they are rarely used for eigenvalue analysis. The objective of this paper is to develop a new multiscale wavelet-based adaptive Galerkin method for eigenvalue analysis. To this end, we employ the hat interpolation wavelets as the basis functions of the finite-dimensional trial function space and formulate a multiresolution analysis approach using the multiscale wavelet-Galerkin method. It is then shown that this multiresolution formulation makes iterative eigensolvers very efficient. The intrinsic difference-checking nature of wavelets is shown to play a critical role in the adaptive analysis. The effectiveness of the present approach will be examined in terms of the total numbers of required nodes and CPU times.

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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Optimum time history analysis of SDOF structures using free scale of Haar wavelet

  • Mahdavi, S.H.;Shojaee, S.
    • Structural Engineering and Mechanics
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    • 제45권1호
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    • pp.95-110
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    • 2013
  • In the recent decade, practical of wavelet technique is being utilized in various domain of science. Particularly, engineers are interested to the wavelet solution method in the time series analysis. Fundamentally, seismic responses of structures against time history loading such as an earthquake, illustrates optimum capability of systems. In this paper, a procedure using particularly discrete Haar wavelet basis functions is introduced, to solve dynamic equation of motion. In the proposed approach, a straightforward formulation in a fluent manner is derived from the approximation of the displacements. For this purpose, Haar operational matrix is derived and applied in the dynamic analysis. It's free-scaled matrix converts differential equation of motion to the algebraic equations. It is shown that accuracy of dynamic responses relies on, access of load in the first step, before piecewise analysis added to the technique of equation solver in the last step for large scale of wavelet. To demonstrate the effectiveness of this scheme, improved formulations are extended to the linear and nonlinear structural dynamic analysis. The validity and effectiveness of the developed method is verified with three examples. The results were compared with those from the numerical methods such as Duhamel integration, Runge-Kutta and Wilson-${\theta}$ method.

비선형 시스템의 안정한 직접 적응 제어를 위한 웨이브렛 신경회로망 (Wavelet Network for Stable Direct Adaptive Control of Nonlinear Systems)

  • 서승진;서재용;원경재;연정흠;전홍태
    • 전자공학회논문지S
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    • 제36S권10호
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    • pp.51-57
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    • 1999
  • 본 논문에서는 웨이브렛 신경회로망을 사용하여 알려지지 않은 비선형 시스템을 안정하게 제어하는 문제를 다룬다. 비선형 시스템의 정확한 제어는 함수를 근사화하는 데 사용되는 함수 근사화기의 정확성과 효율성에 의존한다. 그러므로 기준 함수의 선택이 자유롭고 함수 근사화 능력이 뛰어난 웨이브렛 신경회로망을 비선형 시스템 제어에 이용한다. 초기 웨이브렛 신경회로망 제어기를 설정하기 위해서 먼저 제어기 입력의 시-주파수 특성을 분석해서 웨이브렛 신경회로망 변수인 신축과 이동 값을 구한다. 다음에 Lyapunov 안정성 이론에 기초한 적응 법칙을 사용하여 연결강도를 조절한다. 이 직접 적응 웨이브렛 신경회로망 제어기를 비선형 시스템인 역 진자 시스템을 제어하는데 적용한다.

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