Use of discrete dynamical systems within recurrent neural networks
Project description
Python library to build and use discrete dynamical systems within recurrent neural networks. This library is a user-friendly tool made to use discrete dynamical systems such as Binary ECA, 3 states ECA and CML as a reservoir. Each type of reservoir has its hyper-parameters to enhance the reservoir performance.
Project details
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 Distribution
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 Discrete_Dynamical_Reservoir-0.1.5.tar.gz.
File metadata
- Download URL: Discrete_Dynamical_Reservoir-0.1.5.tar.gz
- Upload date:
- Size: 5.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.10.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
34aa6bc314ebaef1b3a052a5fdedadccfafe3d94c9649a14350f14ad6dc01a3e
|
|
| MD5 |
a25a59356d0514dc17e343b02f8d8e0b
|
|
| BLAKE2b-256 |
1406d875f926f7051239cddddedf11e887bddfdaa195eb39888e521e48227185
|
File details
Details for the file Discrete_Dynamical_Reservoir-0.1.5-py3-none-any.whl.
File metadata
- Download URL: Discrete_Dynamical_Reservoir-0.1.5-py3-none-any.whl
- Upload date:
- Size: 6.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.10.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9e440f5ac42d50d5b938d66b8878a9b09c82711cf1598d4a61274e790f63e4fe
|
|
| MD5 |
4be81e06fe5a6b6aeee60ef775b2980b
|
|
| BLAKE2b-256 |
fe76e19a1da2067c4fc08abb45b435155bc1fac265d39c5adf2c94f93810188e
|