SIMBa: System Identification Methods leveraging Backpropagation
Project description
SIMBa (System Identification Methods leveraging Backpropagation) is an open-source toolbox leveraging the Pytorch Automatic Differentiation framework for stable state-space linear SysID. It allows the user to incorporate prior knowledge (like sparsity patterns of the state-space matrices) during the identification procedure. More details on https://github.com/Cemempamoi/simba.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file simbapy-0.1.2-py3-none-any.whl.
File metadata
- Download URL: simbapy-0.1.2-py3-none-any.whl
- Upload date:
- Size: 18.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.8.16
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f2adc5a857f7cd4679fe97e9138c60c976c56dae62d0d85f9f585b9bd54070e5
|
|
| MD5 |
28f10d165b02274bdde80dd0c8ec3672
|
|
| BLAKE2b-256 |
7072649bc6e7cd6d66a1b7b7d7e10bce103254bf7f45c75999130a330513bac3
|
