Detail publikace

Statistical analysis of wavelet spectrum thresholding rules in order to suppress noise in signal

Originální název

Statistical analysis of wavelet spectrum thresholding rules in order to suppress noise in signal

Anglický název

Statistical analysis of wavelet spectrum thresholding rules in order to suppress noise in signal

Jazyk

en

Originální abstrakt

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.

Anglický abstrakt

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.

Dokumenty

BibTex


@inproceedings{BUT8857,
  author="Pavel {Rajmic}",
  title="Statistical analysis of wavelet spectrum thresholding rules in order to suppress noise in signal",
  annote="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.",
  address="Masarykova univerzita v Brně",
  booktitle="Proceedings of the summer school DATASTAT 03, Folia Fac.Sci.Nat.Univ.Masaryk.Brunensis, Mathematica 15",
  chapter="8857",
  institution="Masarykova univerzita v Brně",
  year="2004",
  month="january",
  pages="1",
  publisher="Masarykova univerzita v Brně",
  type="conference paper"
}