Reservoir computing uses a variety of physical, biologcal or computational processes to increase the non-linear diversity of input data the outputs of which (called the readout) can then be used as inputs for a simpler final machine learning stage.. For example, input data might be used to drive electrical impolses into a semi-chaotic silicon substrate and the output currents measured at multiple points.
Defined on pages 37, 145
Used on pages 6, 37, 124, 145, 146, 147, 387, 584
Also known as readout
Reservoir computing -- main stages