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Algorithmic differentiation improves the computational efficiency of OpenSim-based trajectory optimization of human movement
Algorithmic differentiation (AD) is an alternative to finite differences (FD) for evaluating function derivatives. The primary aim of this study was to demonstrate the computational benefits of using AD instead of FD in OpenSim-based trajectory optimization of human movement. The secondary aim was t...
Enregistré dans:
| Publié dans: | PLoS One |
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| Auteurs principaux: | , , , , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
Public Library of Science
2019
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6797126/ https://ncbi.nlm.nih.gov/pubmed/31622352 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0217730 |
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