RT Journal Article
T1 Uncertainty analysis of ANN based spectral analysis using Monte Carlo method
A1 Salinas, J.R.
A1 García-Lagos, Francisco
A1 Díaz-de-Aguilar, J
A1 Joya-Caparrós, Gonzalo
A1 Sandoval-Hernández, Francisco
K1 Redes neuronales (Informática)
K1 Incertidumbre
K1 Espectroscopía
AB Uncertainty analysis of an Artificial Neural Network (ANN) based method for spectral analysis of asynchronously sampled signals is performed. Main uncer-tainty components contributions, jitter and quantization noise, are considered in order to obtain the signal amplitude and phase uncertainties using Monte Carlo method. The analysis performed identifies also uncertainties main contributions depending on parameters configurations. The analysis is performed simultane-ously with the proposed method and two others: Discrete Fourier Transform (DFT) and Multiharmonic Sine Fitting Method (MSFM), in order to compare them in terms of uncertainty. Results show the proposed method has the same uncertainty as DFT for amplitude values and around double uncertainty in phase values.
PB Springer
YR 2017
FD 2017-06
LK http://hdl.handle.net/10630/13937
UL http://hdl.handle.net/10630/13937
LA eng
NO Salinas J.R., García-Lagos F., de Aguilar J.D., Joya G., Sandoval F. (2017) Uncertainty Analysis of ANN Based Spectral Analysis Using Monte Carlo Method. In: Rojas I., Joya G., Catala A. (eds) Advances in Computational Intelligence. IWANN 2017. Lecture Notes in Computer Science, vol 10305. Springer, Cham
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 21 ene 2026