Data-Driven Learning for Approximating Dynamical Systems Using Deep Neural Networks
In this thesis, a one-step approximation method has been used to produce approximations of two dynamical systems. The two systems considered are a pendulum and a damped dual-mass-spring system. Using a method for a one-step approximation proposed by [15] it is first shown that the state variables of...
| Main Authors: | , |
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| Format: | Others |
| Language: | English |
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KTH, Skolan för teknikvetenskap (SCI)
2021
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| Subjects: | |
| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-297685 |