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Reservoir computing

Reservoir computing

Reservoir computing is a framework for computation derived from recurrent neural network theory that maps input signals into computational spaces through a fixed, nonlinear system called a reservoir.

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Amy Tomlinson Gayle
Amy Tomlinson Gayle approved a suggestion from Golden's AI on 21 Apr, 2021
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The readout is a neural network layer that performs a linear transformation on the output of the reservoir. The weights of the readout layer are, in turn, trained through analyzing the spatiotemporal patterns of the reservoir after excitation by known inputs, and utilizing training methods such as linear regressionlinear regression or ridge regression. Because the readout implementation depends on the reservoir patterns, the details of readout methods are tailored to a specific reservoir.

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