2016
DOI: 10.1007/978-3-319-18842-3
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Linear and Nonlinear Programming

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Cited by 474 publications
(404 citation statements)
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“…To this end, we observe from (2.12) that, for a submacroscopically stable pair (F 0 , G 0 ), the tensor G 0 is a solution of the constrained minimization problem: minimize G → (F 0 , G) subject to the constraint det G det F 0 . The KuhnTucker theorem ( [23], p. 314) implies that, corresponding to the given solution G 0 , there is a number λ 0 for which…”
Section: Submacroscopic Stabilitymentioning
confidence: 99%
“…To this end, we observe from (2.12) that, for a submacroscopically stable pair (F 0 , G 0 ), the tensor G 0 is a solution of the constrained minimization problem: minimize G → (F 0 , G) subject to the constraint det G det F 0 . The KuhnTucker theorem ( [23], p. 314) implies that, corresponding to the given solution G 0 , there is a number λ 0 for which…”
Section: Submacroscopic Stabilitymentioning
confidence: 99%
“…The finite derivative is a special form of a secant correction, used to obtain a special property over a finite interval, see e.g. [10]. In the present case the secant representation is used to provide a higher order correction to the fourth-order representation g q in the form…”
Section: Energy Conservationmentioning
confidence: 99%
“…This concept bears similarity with the notion of a secant representation of derivatives used in quasi Newton methods, see e.g. [10] Chapter 9. The concept was rapidly adopted within computational mechanics, see e.g.…”
Section: Introductionmentioning
confidence: 97%
“…Thus, LSE figures out object position by optimizing sum of squares residual between object and reference points. Linear Least Squares (LLS) and Nonlinear Least Squares (NLS) ( [26], [27], [28] and [29]) are realized and compared. Simulation and experiments have been carried out to verify these proposed methods.…”
Section: Introductionmentioning
confidence: 99%