RT info:eu-repo/semantics/article
T1 Enhanced Monte Carlo-Based Uncertainty Quantification in Electronic Circuits
A1 Dieste Velasco, Mª Isabel
K1 Uncertainty
K1 Electronic circuits
K1 Monte Carlo analysis
K1 Electrónica
K1 Electronics
K1 Circuitos electrónicos
K1 Electronic circuits
AB The determination of measurement uncertainty is of paramount importance in defining the range of values assigned to a given response variable. In electronic circuits, this is a challenging task that still needs further development. Difficulties associated with repeated measurements and the inherent variability of components make it difficult to determine uncertainty unless a large number of measurements are taken, which increases costs. Furthermore, due to the strong nonlinear characteristics of most electronic circuits and the difficulty in determining a differentiable expression, it is not feasible to apply uncertainty propagation. An alternative for modeling uncertainty is the Monte Carlo method, as proposed by the Guide for the Expression of Measurement Uncertainty (GUM and GUM-S1). However, when the probability distribution of the response variables significantly deviates from normal, the GUM-S1 method may lead to inaccurate results. This study proposes a new Monte Carlo-based method to quantify measurement uncertainty in electronic circuits and includes a comparative study of GUM, GUM-S1, and the proposed method. It is shown that uncertainty can be determined more accurately with the proposed method when normality cannot be assumed. The proposed method is applied to two analog circuits: a Sallen-Key filter and a low-signal amplifier.
PB Springer
SN 0923-8174
YR 2025
FD 2025-10
LK https://hdl.handle.net/10259/11193
UL https://hdl.handle.net/10259/11193
LA eng
NO Open access funding provided by FEDER European Funds and the Junta de Castilla y León under the Research and Innovation Strategy for Smart Specialization (RIS3) of Castilla y León 2021-2027. Open access funding provided by the CRUE-CSIC agreement with Springer Nature, the FEDER European Funds, and the Junta de Castilla y León under the Research and Innovation Strategy for Smart Specialization (RIS3) of Castilla y León 2021–2027.
DS Repositorio Institucional de la Universidad de Burgos
RD 17-abr-2026