Comparison of Backpropagation and Kalman Filter-based Training for Neural Networks

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Authors

This work describes and compares the backpropagation algorithm with the extended Kalman filter (EKF), a second-order training method which can be applied to the problem of learning neural network parameters and is known to converge in only a few iterations. The algorithms are compared with respect to their effectiveness and speed of convergence using simulated data for both, a regression and a classification task.

OriginalspracheEnglisch
Titel2021 25th International Conference on System Theory, Control and Computing (ICSTCC) : October 20 – 23, 2021 Iași, ROMANIA, Proceedings
HerausgeberLavinia Ferariu, Mihaela-Hanako Matcovschi, Florina Ungureanu
Anzahl der Seiten8
ErscheinungsortPiscataway
VerlagInstitute of Electrical and Electronics Engineers Inc.
Erscheinungsdatum20.10.2021
Seiten234-241
ISBN (Print)978-1-6654-3055-5
ISBN (elektronisch)978-1-6654-1496-8
DOIs
PublikationsstatusErschienen - 20.10.2021
Veranstaltung25th International Conference on System Theory, Control and Computing - Iasi, Rumänien
Dauer: 20.10.202123.10.2021
Konferenznummer: 25
https://ieeexplore.ieee.org/xpl/conhome/9607028/proceeding

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