Detail publikace

Wavelet Significance Testing with Respect to GWN Background: Monte Carlo Simulation Usage

Originální název

Wavelet Significance Testing with Respect to GWN Background: Monte Carlo Simulation Usage

Anglický název

Wavelet Significance Testing with Respect to GWN Background: Monte Carlo Simulation Usage

Jazyk

en

Originální abstrakt

The paper deals with significance testing of wavelet coefficients. We investigate the test of wavelet power spectrum with respect to the Gaussian white noise background spectrum from two perspectives of calculating significance level: with the use of chi-square distribution and with the use of Monte Carlo simulation. Our experiment is performed on a special kind of synthetic signal in which the frequency component is changing during time. We investigate the level of variance of the signal and the significance risk. We describe the advantages and disadvantages of both approaches and formulate recommendations for using time-frequency testing.

Anglický abstrakt

The paper deals with significance testing of wavelet coefficients. We investigate the test of wavelet power spectrum with respect to the Gaussian white noise background spectrum from two perspectives of calculating significance level: with the use of chi-square distribution and with the use of Monte Carlo simulation. Our experiment is performed on a special kind of synthetic signal in which the frequency component is changing during time. We investigate the level of variance of the signal and the significance risk. We describe the advantages and disadvantages of both approaches and formulate recommendations for using time-frequency testing.

Dokumenty

BibTex


@inproceedings{BUT134460,
  author="Eva {Klejmová} and Tobiáš {Malach} and Jitka {Poměnková}",
  title="Wavelet Significance Testing with Respect to GWN Background: Monte Carlo Simulation Usage",
  annote="The paper deals with significance testing of wavelet coefficients.  We investigate the test of  wavelet power spectrum with respect to the Gaussian white noise background  spectrum from two  perspectives of calculating significance level: with the use of chi-square  distribution and with the use of Monte Carlo simulation. Our experiment  is performed on a special kind of synthetic signal in which the frequency component is  changing   during time. We  investigate  the level of variance of the signal and the significance risk. We  describe the advantages and disadvantages of both approaches and  formulate recommendations for using time-frequency testing.",
  booktitle="Proceedings of 27th international conference Radioelektronika 2017",
  chapter="134460",
  doi="10.1109/RADIOELEK.2017.7937593",
  howpublished="online",
  year="2017",
  month="april",
  pages="1--4",
  type="conference paper"
}