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Convergence properties of the modified subgradient method of camerini et al

✍ Scribed by Sehun Kim; Hyunsil Ahn


Publisher
John Wiley and Sons
Year
1990
Tongue
English
Weight
243 KB
Volume
37
Category
Article
ISSN
0894-069X

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Convergence properties of the generalise
✍ Torsten SΓΆderstrΓΆm πŸ“‚ Article πŸ“… 1974 πŸ› Elsevier Science 🌐 English βš– 816 KB

Generalized least squares identification may be interpreted as a loss .function minimization, but more than one local minimum may exist, depending on the signal to noise ratio, and undesired estimates can result. Summary--Convergence properties of the generalized least squares method are analyzed.