Publication result detail

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

RAJMIC, P.

Original Title

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

English Title

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

Type

Paper in proceedings (conference paper)

Original Abstract

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.

English abstract

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.

Key words in English

signal denoising, statistical thresholding, wavelets

Authors

RAJMIC, P.

RIV year

2011

Released

01.01.2004

Publisher

Masarykova univerzita v Brně

Location

Brno

ISBN

80-210-3564-1

Book

Proceedings of the summer school DATASTAT 03, Folia Fac.Sci.Nat.Univ.Masaryk.Brunensis, Mathematica 15

Pages from

1

Pages count

16

BibTex

@inproceedings{BUT8857,
  author="Pavel {Rajmic}",
  title="Statistical analysis of wavelet spectrum thresholding rules in order to suppress noise in signal",
  booktitle="Proceedings of the summer school DATASTAT 03, Folia Fac.Sci.Nat.Univ.Masaryk.Brunensis, Mathematica 15",
  year="2004",
  pages="16",
  publisher="Masarykova univerzita v Brně",
  address="Brno",
  isbn="80-210-3564-1"
}