A configurable analog VLSI neural network with spiking neurons and self-regulating plastic synapses

Part of Advances in Neural Information Processing Systems 20 (NIPS 2007)

Authors

Massimiliano Giulioni, Mario Pannunzi, Davide Badoni, Vittorio Dante, Paolo Giudice

Abstract

We summarize the implementation of an analog VLSI chip hosting a network of 32 integrate-and-fire (IF) neurons with spike-frequency adaptation and 2,048 Hebbian plastic bistable spike-driven stochastic synapses endowed with a self-regulating mechanism which stops unnecessary synaptic changes. The synaptic matrix can be flexibly configured and provides both recurrent and AER-based connectivity with external, AER compliant devices. We demonstrate the ability of the network to efficiently classify overlapping patterns, thanks to the self-regulating mechanism.