TutorialsΒΆ

We have prepared a collection of Jupyter (IPython) notebooks that show how to use the package.

You can view them online or download Python scripts:

https://github.com/TUD-STKS/PyRCN/tree/main/examples

The notebook PyRCN_Intro or its corresponding Python script show how to construct different RCNs with building blocks.

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The notebook Impulse responses is an interactive tool to demonstrate the impact of different hyper-parameters on the impulse responses of an ESN.

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The Jupyter notebook digits or its corresponding Python script show how to set up an ESN for a small hand-written digit recognition experiment.

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Fore more advanced examples, please have a look at our Automatic Music Transcription Repository, in which we provide an entire feature extraction, training and test pipeline for multipitch tracking and for note onset detection using PyRCN. This is currently transferred to this repository.