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Use of the wavelet method for analyzing electrochemical noise data
Author(s) -
Duran O.,
Vera E.,
Ortiz C. A.,
Heyn A.
Publication year - 2007
Publication title -
materials and corrosion
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.487
H-Index - 55
eISSN - 1521-4176
pISSN - 0947-5117
DOI - 10.1002/maco.200704094
Subject(s) - electrochemical noise , wavelet , noise (video) , fast fourier transform , computer science , wavelet transform , fourier transform , toolbox , transformation (genetics) , algorithm , harmonic wavelet transform , electronic engineering , biological system , electrochemistry , wavelet packet decomposition , electrode , artificial intelligence , mathematics , engineering , mathematical analysis , physics , chemistry , gene , image (mathematics) , biology , biochemistry , quantum mechanics , programming language
This research paper shows the application of the mathematical tool “wavelet's” to be used in the interpretation and analysis of electrochemical noise signals. The Fast Fourier Transformation (FFT) is one of the most commonly used techniques for analyzing electrochemical noise. But the application of this methodology to the analysis of stochastic signals does not allow their interpretation in a suitable way. The wavelet's methodology carries out the analysis by means of the construction of finite base functions. In several studies, it has been found out that the function that is closest to the electrochemical oscillations is the one called “coiflets,” which presents a similar geometry to what it is observed when an ionic–electronic interchange occurs during an electrochemical interphase. The analysis that appears here was implemented using the toolbox “LabView™.”