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Monte Carlo uncertainty analysis of an ANN-based spectral analysis method

  • José Ramón SalinasEmail author
  • Francisco García-Lagos
  • Javier Diaz de Aguilar
  • Gonzalo Joya
  • Francisco Sandoval
IWANN2017: Learning algorithms with real world applications
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Abstract

This work presents the uncertainty analysis of an artificial neural network (ANN)-based method, called multiharmonic ANN fitting method (MANNFM), which is able to obtain, at a metrological level, the spectrum of asynchronously sampled periodical signals. For sinusoidal and harmonic content signals, jitter and quantization noise contributions to uncertainty are considered in order to obtain amplitude and phase uncertainties using Monte Carlo method. The analysis performed identifies also both contributions to uncertainty for different parameters laboratory configurations. The analysis is performed simultaneously with our method and two others: discrete Fourier transform (DFT), for synchronously sampled signals, and multiharmonic sine-fitting method (MSFM), for asynchronously sampled signals, in order to compare them in terms of uncertainty. Regarding asynchronous methods, results show that MANNFM provides the same uncertainties than MSFM, with the advantage of a simpler implementation. Regarding asynchronous and synchronous methods comparison, results for sinusoidal signals show that MANNFM has the same uncertainty as DFT for amplitude and higher uncertainty for phase values; for signals with harmonic content, amplitude conclusions maintain but, regarding phase, both MANNFM and DFT uncertainties become closer as the frequency increases, which implies, in fact, that when synchronous sampling is not possible, spectrum analysis can be performed with asynchronous methods without incurring in uncertainty increases.

Keywords

Sine-fitting methods Spectral analysis ADALINE Digital measurement Uncertainty Monte Carlo 

Notes

Acknowledgements

This work was partially supported by the Universidad de Malaga - Campus de Excelencia Andalucia-Tech.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.Grupo ISIS, Dpto. Tecnología Electrónica, ETSI TelecomunicaciónUniversidad de MálagaMálagaSpain
  2. 2.Centro Español de Metrología (CEM)Tres CantosSpain

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