Definition of Reservoir Computing

Reservoir Computing (RC) is a paradigm for a fast one-shot training of Recurrent Neural Networks (RNNs). Probably the best known RC architecture is the Echo State Network (ESN) by Herbert Jaeger.

The Scholarpedia article about Echo State Networks gives an excellent introduction to the topic of Echo State Networks.

In a broader sense, the Extreme Learning Machine (ELM) as a closely related architecture also counts to RC, although it is a feed-forward network. The training paradigm is similar, and PyRCN aims to unify the development of ESNs and ELMs.

Many examples can be found in the PyRCN repository. Some useful examples can also be found in the PyRCN repository with many Jupyter notebooks.

PyRCN is inspired by ReservoirPy, another RC toolbox with a different scope. We recommend to check their examples and tutorials.