New Hardware for Massive Neural Networks

Part of Neural Information Processing Systems 0 (NIPS 1987)

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Authors

Darryl Coon, A. Perera

Abstract

Transient phenomena associated with forward biased silicon p + - n - n + struc(cid:173) tures at 4.2K show remarkable similarities with biological neurons. The devices play a role similar to the two-terminal switching elements in Hodgkin-Huxley equivalent circuit diagrams. The devices provide simpler and more realistic neuron emulation than transistors or op-amps. They have such low power and current requirements that they could be used in massive neural networks. Some observed properties of simple circuits containing the devices include action potentials, refractory periods, threshold behavior, excitation, inhibition, summation over synaptic inputs, synaptic weights, temporal integration, memory, network connectivity modification based on experience, pacemaker activity, firing thresholds, coupling to sensors with graded sig(cid:173) nal outputs and the dependence of firing rate on input current. Transfer functions for simple artificial neurons with spiketrain inputs and spiketrain outputs have been measured and correlated with input coupling.