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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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An early example of reservoir computing, the context reverberation network architecturenetwork architecture has an input layer which feeds into a dimensional dynamical systems read out by a trainable single-layer perceptron. In this network, two kinds of dynamical systems were described:

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