A Python Package For System Identification Using NARMAX Models
-
Updated
Nov 12, 2024 - Jupyter Notebook
#
narmax
Here are 7 public repositories matching this topic...
Machine learning library for symbolic fitting: the unknown system/function is described via NARMAX algebraic expressions being linear combinations of arbitrary non-linear terms provided by the user (like 0.2x²+0.7sin(x) or x[k-1]*y[k-4]^2).
machine-learning symbolic-regression gpu-acceleration equation-solver least-square-regression narmax
-
Updated
May 14, 2024 - Python
Algorithms for Lasso estimation of NARMAX models.
-
Updated
Dec 30, 2019 - Julia
GUI for System Identification using NARX and NARMAX models
-
Updated
Dec 11, 2024 - Python
A MatLab package for System Identification using linear and nonlinear auto-regresive models (N)AR, (N)ARX and (N)ARMAX models
machine-learning time-series dynamical-systems nonlinear-dynamics system-identification dynamical-modeling narx narmax time-series-forecasting forward-selection autoregressive-models orthogonal-forward-regression
-
Updated
Dec 4, 2024 - MATLAB
Experiments and derivations for ACC2022 paper on variational message passing for online NARMAX identification.
-
Updated
Apr 22, 2022 - Jupyter Notebook
Experiments and derivations for CDC2022 paper on message passing-based inference for NARMAX system identification.
-
Updated
Aug 26, 2022 - Jupyter Notebook
Improve this page
Add a description, image, and links to the narmax topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the narmax topic, visit your repo's landing page and select "manage topics."