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  • One of the most important applications of the wavelet transform is denoising (suppresing noise in signals). The principle of this technique is described in the paper. Statistical properties of so-called thresholding rules used in denoising in the presence of gaussian (normally distributed) noise are also introduced and compared.
  • One of the most important applications of the wavelet transform is denoising (suppresing noise in signals). The principle of this technique is described in the paper. Statistical properties of so-called thresholding rules used in denoising in the presence of gaussian (normally distributed) noise are also introduced and compared. (en)
Title
  • Statistical analysis of wavelet spectrum thresholding rules in order to suppress noise in signal
  • Statistical analysis of wavelet spectrum thresholding rules in order to suppress noise in signal (en)
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  • Statistical analysis of wavelet spectrum thresholding rules in order to suppress noise in signal
  • Statistical analysis of wavelet spectrum thresholding rules in order to suppress noise in signal (en)
skos:notation
  • RIV/00216305:26220/04:PU38279!RIV11-MSM-26220___
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  • P(GA102/03/0762), V, Z(MSM 262200011), Z(MSM 262200022)
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  • 588000
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  • RIV/00216305:26220/04:PU38279
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  • signal denoising, statistical thresholding, wavelets (en)
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  • [997B22E090C0]
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  • Svratka
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  • Brno
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  • Proceedings of the summer school DATASTAT 03, Folia Fac.Sci.Nat.Univ.Masaryk.Brunensis, Mathematica 15
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  • Rajmic, Pavel
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number of pages
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  • Masarykova univerzita v Brně
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  • 80-210-3564-1
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  • 26220
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