Data-driven identification of nonlinear normal modes via physics-integrated deep learning
- 7 October 2021
- journal article
- research article
- Published by Springer Nature in Nonlinear Dynamics
- Vol. 106 (4) , 3231-3246
Abstract
No abstract availableKeywords
Funding Information
- Defense Sciences Office, DARPA
- Michigan Technological University
This publication has 49 references indexed in Scilit:
- Spectral analysis of nonlinear flowsJournal of Fluid Mechanics, 2009
- Distilling Free-Form Natural Laws from Experimental DataScience, 2009
- The Illusion of Invariant Quantities in Life HistoriesScience, 2005
- Modal identification of output-only systems using frequency domain decompositionSmart Materials and Structures, 2001
- Artificial neural networks for solving ordinary and partial differential equationsIEEE Transactions on Neural Networks, 1998
- Normal Modes for Non-Linear Vibratory SystemsJournal of Sound and Vibration, 1993
- Experimental modal analysis for dynamic models of spacecraftJournal of Guidance, Control, and Dynamics, 1991
- Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networksNeural Networks, 1990
- Modal method for analysis of free rotations of spacecraft.AIAA Journal, 1967
- The Normal Modes of Nonlinear n-Degree-of-Freedom SystemsJournal of Applied Mechanics, 1962