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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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Reservoir computing is an approach to recurrent neural networkrecurrent neural network design and training which maps input signals into higher dimensional computational spaces through a fixed, nonlinear system called a reservoir. The reservoir is treated as a black box from which a simple readout mechanism is trained to read the state of the reservoir and map it to the desired output. Reservoir computing is suited for temporal or sequential data processing. This computing setup features two key elements: a dynamical system that can respond to inputs (a reservoir) and a readout layer used to analyze the state of the system.

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