As of this date, the module does not handle (is not aware) of sparse matrices. It would be prudent for all system matrices from FEA to be considered sparse. This necessitates the conversion to sparse format. The following notes were made in a notebook earlier. The first experience was in using mode_expansion_from_model.
FSID is a toolbox with scripts which estimates linear multi-input multi-output state-space models from sample data using frequency-domain subspace algorithms. Algorithms which estimate models based on samples of the transfer function matrix as well as frequency domain input and output vectors are provided. The algorithms can be used for discrete-time models, continuous-time models as well as for approximation of rational matrices from samples corresponding to arbitrary points in the complex plane.
This project deals with system identification and machine learning of large-scale deformable mirrors used in adaptive optics. I have submitted two papers that deal with this important problem. The approaches can be generalized two other problems of estimating large-scale system with the dynamics described by partial differential equations.
Currently, the codecogs API is used for displaying math however it is not aligned properly with the text.