Metadata-Version: 2.4
Name: reservoir-computing-benedictchen
Version: 1.0.0
Summary: Echo State Networks and Liquid State Machines - Revolutionary temporal processing without training recurrent weights
Project-URL: Funding, https://www.paypal.com/cgi-bin/webscr?cmd=_s-xclick&hosted_button_id=WXQKYYKPHWXHS
Author-email: Benedict Chen <benedict@benedictchen.com>
Maintainer-email: Benedict Chen <benedict@benedictchen.com>
License: Custom Non-Commercial License with Donation Requirements
License-File: LICENSE
Keywords: artificial-intelligence,echo-state-networks,liquid-state-machines,machine-learning,recurrent-neural-networks,reservoir-computing,spiking-neural-networks,temporal-processing
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: Other/Proprietary License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.9
Requires-Dist: matplotlib>=3.5.0
Requires-Dist: networkx>=2.6
Requires-Dist: numpy>=1.21.0
Requires-Dist: scikit-learn>=1.0.0
Requires-Dist: scipy>=1.7.0
Provides-Extra: dev
Requires-Dist: black>=23.0; extra == 'dev'
Requires-Dist: isort>=5.12; extra == 'dev'
Requires-Dist: mypy>=1.5; extra == 'dev'
Requires-Dist: ruff>=0.1.0; extra == 'dev'
Provides-Extra: test
Requires-Dist: hypothesis>=6.70; extra == 'test'
Requires-Dist: pytest-cov>=4.0; extra == 'test'
Requires-Dist: pytest-mock>=3.10; extra == 'test'
Requires-Dist: pytest>=7.0; extra == 'test'
Description-Content-Type: text/markdown

# Reservoir Computing (Benedict Chen Edition)

🌊 Echo State Networks & Liquid State Machines - Production implementations of Jaeger (2001) & Maass (2002)

## Quick Start

```python
from reservoir_computing_benedictchen import EchoStateNetwork, LiquidStateMachine

# Echo State Network
esn = EchoStateNetwork(reservoir_size=100, spectral_radius=0.95)

# Liquid State Machine  
lsm = LiquidStateMachine(n_liquid=200)
```

## Installation

```bash
pip install reservoir-computing-benedictchen
```

## Support Benedict's Work

💰 **[Buy Benedict a beer](https://www.paypal.com/cgi-bin/webscr?cmd=_s-xclick&hosted_button_id=WXQKYYKPHWXHS)** - Support open source AI research!

Author: **Benedict Chen** (benedict@benedictchen.com)
