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  • Basics of wavelet expansions and wavelet de-noising (Donoho-Johnstone) are explained following the analogy with the classical Fourier analysis and using general concepts in the $L_2$ function space as the common background. Also the fundamental relations of the multiresolution analysis are derived. They yield a recurrent procedure allowing us to raise/lower the level of the wavelet approximation step by step. Figures of some commonly used wavelet shapes and examples of practical data analysis demonstrate the topics.
  • Basics of wavelet expansions and wavelet de-noising (Donoho-Johnstone) are explained following the analogy with the classical Fourier analysis and using general concepts in the $L_2$ function space as the common background. Also the fundamental relations of the multiresolution analysis are derived. They yield a recurrent procedure allowing us to raise/lower the level of the wavelet approximation step by step. Figures of some commonly used wavelet shapes and examples of practical data analysis demonstrate the topics. (en)
Title
  • Fast Algorithms of Fourier and Hartley transform and their implementation in MATLAB
  • Fast Algorithms of Fourier and Hartley transform and their implementation in MATLAB (en)
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  • Fast Algorithms of Fourier and Hartley transform and their implementation in MATLAB
  • Fast Algorithms of Fourier and Hartley transform and their implementation in MATLAB (en)
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  • RIV/00216224:14310/98:00000669!RIV/2002/GA0/143102/N
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  • 185
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  • P(GA201/96/0665)
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  • 767540
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  • RIV/00216224:14310/98:00000669
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  • fast Fourier transform; fast Hartley transform; factorization of matrices; generalized Kronecker product of matrices; performance tests (en)
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  • [58F3B04502DE]
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  • Brno (Czech Rep.)
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  • Brno (Czech Rep.)
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  • Proceedings of Summer School DATASTAT'97
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  • Veselý, Vítězslav
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  • Masaryk University
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  • 80-210-1950-6
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  • 14310
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