Requires python 3.8+
Incremental Multiresolution Dynamic Mode Decomposition (i-mrDMD) is the incremental counterpart of Multiresolution Dynamic Mode Decomposition (mrDMD) that incrementally updates the previously computed mrDMD results.
mrDMD is a technique used to analyze complex, time-dependent systems by decomposing their dynamics across multiple temporal scales. It is an extension of Dynamic Mode Decomposition (DMD), which extracts coherent spatiotemporal patterns and their associated dynamics from high-dimensional datasets.
- Niklas Kühl (2024). Incremental Singular Value Decomposition Example (https://www.mathworks.com/matlabcentral/fileexchange/124815-incremental-singular-value-decomposition-example), MATLAB Central File Exchange. Retrieved November 17, 2024.
- S. Shilpika et al., "A Multi-Level, Multi-Scale Visual Analytics Approach to Assessment of Multifidelity HPC Systems," 2024 IEEE 24th International Symposium on Cluster, Cloud and Internet Computing (CCGrid), Philadelphia, PA, USA, 2024, pp. 478-488, doi: 10.1109/CCGrid59990.2024.00060.
- Kutz, J. N., Fu, X., and Brunton, S. L., 2016, “Multiresolution Dynamic Mode Decomposition”, SIAM J. Appl. Dyn. Syst., 15 (2), pp. 713-735.
- B. W. Brunton, L. A. Johnson, J. G. Ojemann, and J. N. Kutz, “Extracting spatial–temporal coherent patterns in large-scale neural recordings using dynamic mode decomposition,” Journal of Neuroscience Methods, vol. 258, 2016.
- Code Modified from https://www.mathworks.com/matlabcentral/fileexchange/124815-incremental-singular-value-decomposition-example & https://humaticlabs.com/blog/mrdmd-python/