Electron Paramagnetic Resonance, Optimization and Automatic Differentiation

机译：电子顺磁共振，优化和自动微分

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This chapter describes an optimization problem applied to electron paramagnetic resonance spectroscopy. Levenberg-Marquardt fails to converge using a divided differences Jacobian approximation in single precision, while it succeeds using Odyssee-generated forward mode Jacobian values. In double precision, the optimizer returns a smaller "minimum" objective function with AD compared to DD in 46% more CPU time.

机译：本章介绍了应用于电子顺磁共振波谱的优化问题。 Levenberg-Marquardt无法使用单精度的除差Jacobian逼近进行收敛，而使用Odyssee生成的前向模式Jacobian值则能够成功收敛。以双精度计算，与DD相比，优化器使用AD返回的“目标”函数更小，而DD的CPU时间却增加了46％。

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来源
《Third International Conference on Automatic Differentiation; Jun, 2000; Cote d'Azur, France》|2002年|p.99-106|共8页
会议地点 Cote dAzur(FR)
作者
Edgar J. Soulie; Christele Faure; Theo Berclaz; Michel Geoffroy;
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Service de chimie moleculaire CEA-DSM-DRECAM, CEA Saclay, 91191 Gif-sur-Yvette Cedex France;

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原文格式 PDF
正文语种 eng
中图分类自动化技术、计算机技术;
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Electron Paramagnetic Resonance, Optimization and Automatic Differentiation

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