King's College London

University College London

Denise Gorse

John G Taylor

Trevor G Clarkson

Neural processing devices for handling real-valued inputs

A neuron for use in a neural processing network, comprises a memory having a plurality of storage locations at each of which a number representing a probability is stored, each of the storage locations being selectively addressable to cause the contents of the location to be read to an input of a comparator. A noise generator inputs to the comparator a random number representing noise. At an output of the comparator an output signal appears having a first or second value depending on the values of the numbers received from the addressed storage location and the noise generator, the probability of the output signal having a given one of the first and second values being determined by the number at the addressed location. Preferably the neuron receives from the environment signals representing success or failure of the network, the value of the number stored at the addressed location being changed in such a way as to increase the probability of the successful action if a success signal is received, and to decrease the probability of the unsuccessful action if a failure signal is received.

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Essex, United Kingdom

Denise Gorse