Publicación:
System identification models' fit using error histogram analysis and the Hampel filter as computational tools

dc.contributor.author Risco R. es_PE
dc.contributor.author Perez D. es_PE
dc.contributor.author Casaverde L. es_PE
dc.date.accessioned 2024-05-30T23:13:38Z
dc.date.available 2024-05-30T23:13:38Z
dc.date.issued 2020
dc.description.abstract In the present investigation, we use the error histogram analysis as a computational tool to define whether the model resulting from a system identification process should continue to be fitted, and the Hampel filter for the elimination of outliers as a tool that also avoids on model over-parameterization. To do this, we use three data sets from a four-cylinder BMW diesel engine, to identify a linear model, and then, with that model, analyze the error and its histogram in a data set (without noise, with noise and with outliers). The analysis of the histogram of the error was found to be a useful tool for detecting white noise and helps to avoid overfitting, in addition to the fact that the Hampel filter allowed detecting and eliminating atypical samples. The software used was MATLAB. © 2020 IEEE.
dc.description.sponsorship Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - Concytec
dc.identifier.doi https://doi.org/10.1109/INTERCON50315.2020.9220230
dc.identifier.scopus 2-s2.0-85095422553
dc.identifier.uri https://hdl.handle.net/20.500.12390/2497
dc.language.iso eng
dc.publisher Institute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020
dc.rights info:eu-repo/semantics/openAccess
dc.subject Outliers
dc.subject ARMAX es_PE
dc.subject ARX es_PE
dc.subject Hampel es_PE
dc.subject Identification es_PE
dc.subject.ocde http://purl.org/pe-repo/ocde/ford#2.02.04
dc.title System identification models' fit using error histogram analysis and the Hampel filter as computational tools
dc.type info:eu-repo/semantics/article
dspace.entity.type Publication
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