Insights Into Algorithms for Separable Nonlinear Least Squares Problems

Separable nonlinear least squares (SNLLS) problems have attracted interest in a wide range of research fields such as machine learning, computer vision, and signal processing. During the past few decades, several algorithms, including the joint optimization algorithm, alternated least squares (ALS)...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on image processing Jg. 30; S. 1207 - 1218
Hauptverfasser:	Chen, Guang-Yong, Gan, Min, Wang, Shuqiang, Chen, C. L. Philip
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Analytical models Autoregressive models Autoregressive processes Bundle adjustment Computer vision Image restoration Jacobian matrices Least squares Machine learning Optimization parameter estimation Partitioning algorithms Radial basis function RBF-AR model Robustness Robustness (mathematics) separable nonlinear least-squares problem Signal processing Signal processing algorithms Variable projection
ISSN:	1057-7149, 1941-0042, 1941-0042
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!