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Minimierungsprobleme ohne Nebenbedingungen

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Part of the book series: Mathematik im Fokus ((MIF))

Zusammenfassung

Im Folgenden werden wir die Grundprinzipien der numerischen Approximation einer Kurve des steilsten Abstiegs (siehe Abschn. 1.2) bei der numerischen Approximation von

$$\displaystyle\boldsymbol{Y}_{{\varepsilon}}(\textbf{\textbullet},\tilde{\varphi}):[\, 0,\infty)\to\mathbb{R}^{n}\,,\quad t\mapsto\boldsymbol{Y}_{{\varepsilon}}(t,\tilde{\varphi})$$

gegeben durch

$$\displaystyle\boldsymbol{Y}_{{\varepsilon}}(t,\tilde{\varphi})=\boldsymbol{y}_{0}-\int\limits _{0}^{{t}}\boldsymbol{\nabla}f(\boldsymbol{Y}_{\varepsilon}(\tau,\tilde{\varphi}))\,\operatorname{d}\tau+\varepsilon\left(\boldsymbol{B}_{t}(\tilde{\varphi})-\boldsymbol{B}_{0}(\tilde{\varphi})\right)\,,\quad t\in[\, 0,\infty)\,,$$

verwenden.

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Correspondence to Stefan Schäffler .

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© 2014 Springer-Verlag Berlin Heidelberg

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Schäffler, S. (2014). Minimierungsprobleme ohne Nebenbedingungen. In: Globale Optimierung. Mathematik im Fokus. Springer Spektrum, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41767-2_4

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