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Neural Networks

Liquid State Machines

A pool of spiking neurons whose rich dynamics make a signal easy to read off.

Feed a signal into a randomly connected reservoir of spiking neurons and its dynamics project the input into a high-dimensional space. Only a simple readout layer is trained; the reservoir itself is left alone.

Because training is cheap and the model is inherently temporal, the approach is of continuing interest for streaming signals and for neuromorphic hardware.

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