Robust and Scalable Methods for the Dynamic Mode Decomposition

The dynamic mode decomposition (DMD) is a broadly applicable dimensionality reduction algorithm that decomposes a matrix of time-series data into a product of a matrix of exponentials, representing Fourier-like time dynamics, and a matrix of coefficients, representing spatial structures. This interp...

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Bibliographic Details
Main Authors:	Aravkin, A. (Author), Askham, T. (Author), Kutz, J.N (Author), Zheng, P. (Author)
Format:	Article
Language:	English
Published:	Society for Industrial and Applied Mathematics Publications 2022
Subjects:	Dimensionality reduction algorithms dynamic mode decomposition Dynamic mode decomposition Dynamic mode decompositions Exponentials Fourier series matrix Matrix algebra Open source software Open systems Principal component analysis Robust methods robust statistics Robust statistics Scalability scalable algorithms Scalable algorithms Scalable methods Software testing Stochastic systems Time dynamic Variable projection
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Robust and Scalable Methods for the Dynamic Mode Decomposition

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