Encoding temporal structure in probabilistic RAM nets

The authors show how both gradient descent and reinforcement training can be used to teach a recurrent probabilistic RAM (pRAM) net to classify binary strings of arbitrary length, and how a form of reinforcement training can be used with 'leaky integrator' pRAM nodes to enable them to store complex temporal sequences.<
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