• 제목/요약/키워드: hat interpolation wavelet

검색결과 2건 처리시간 0.016초

DECAY CHARACTERISTICS OF THE HAT INTERPOLATION WAVELET COEFFICIENTS IN THE TWO-DIMENSIONAL MULTIRESOLUTION REPRESENTATION

  • KWON KIWOON;KIM YOON YOUNG
    • 대한수학회지
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    • 제42권2호
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    • pp.305-334
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    • 2005
  • The objective of this study is to analyze the decay characteristics of the hat interpolation wavelet coefficients of some smooth functions defined in a two-dimensional space. The motivation of this research is to establish some fundamental mathematical foundations needed in justifying the adaptive multiresolution analysis of the hat-interpolation wavelet-Galerkin method. Though the hat-interpolation wavelet-Galerkin method has been successful in some classes of problems, no complete error analysis has been given yet. As an effort towards this direction, we give estimates on the decaying ratios of the wavelet coefficients at children interpolation points to the wavelet coefficient at the parent interpolation point. We also give an estimate for the difference between non-adaptively and adaptively interpolated representations.

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.