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)...

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Vydané v:	IEEE transactions on image processing Ročník 30; s. 1207 - 1218
Hlavní autori:	Chen, Guang-Yong, Gan, Min, Wang, Shuqiang, Chen, C. L. Philip
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	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
On-line prístup:	Získať plný text
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