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  • In this article there is described a simple algorithm for peak recognition. It is primarily intended to be used for sound signal analysis. It is easy to find the highest value in spectrum, but the problem is to find other peaks. Then it is important to define what is considered to be a peak and what is the expected peak width (or FWHM, full width at half maximum). The peak usually has Gaussian bell shape but due to errors in measurement it also often contains noise. The noise prevents some naive algorithms to work properly because they may find many false maximums within one peak. The approach described in this article is based on Gaussian convolution smoothing of the whole spectrum which makes possible to find peak and its beginning and end. Then such interval is replaced by zeros and another peak can be found. The cycle goes on until desired number of peaks is found.
  • In this article there is described a simple algorithm for peak recognition. It is primarily intended to be used for sound signal analysis. It is easy to find the highest value in spectrum, but the problem is to find other peaks. Then it is important to define what is considered to be a peak and what is the expected peak width (or FWHM, full width at half maximum). The peak usually has Gaussian bell shape but due to errors in measurement it also often contains noise. The noise prevents some naive algorithms to work properly because they may find many false maximums within one peak. The approach described in this article is based on Gaussian convolution smoothing of the whole spectrum which makes possible to find peak and its beginning and end. Then such interval is replaced by zeros and another peak can be found. The cycle goes on until desired number of peaks is found. (en)
Title
  • Simple algorithm for peak recognition in frequency spectrum
  • Simple algorithm for peak recognition in frequency spectrum (en)
skos:prefLabel
  • Simple algorithm for peak recognition in frequency spectrum
  • Simple algorithm for peak recognition in frequency spectrum (en)
skos:notation
  • RIV/00216305:26110/08:PU80096!RIV10-GA0-26110___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA103/06/1711)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 394738
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26110/08:PU80096
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • peak recognition, frequency analysis, python, scipy (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [6BB6125682A5]
http://linked.open...v/mistoKonaniAkce
  • Bratislava
http://linked.open...i/riv/mistoVydani
  • Neuveden
http://linked.open...i/riv/nazevZdroje
  • VÝSKUMNÉ A EDUKAČNÉ AKTIVITY NA KATEDRÁCH FYZIKY TECHNICKÝCH UNIVERZÍT
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Martinek, Jan
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Neuveden
https://schema.org/isbn
  • 978-80-227-2887-4
http://localhost/t...ganizacniJednotka
  • 26110
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