A Configurable Analog VLSI Neural Network with Spiking Neurons and Self-Regulating Plastic Synapses
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.
Cite
Text
Giulioni et al. "A Configurable Analog VLSI Neural Network with Spiking Neurons and Self-Regulating Plastic Synapses." Neural Information Processing Systems, 2007.Markdown
[Giulioni et al. "A Configurable Analog VLSI Neural Network with Spiking Neurons and Self-Regulating Plastic Synapses." Neural Information Processing Systems, 2007.](https://mlanthology.org/neurips/2007/giulioni2007neurips-configurable/)BibTeX
@inproceedings{giulioni2007neurips-configurable,
title = {{A Configurable Analog VLSI Neural Network with Spiking Neurons and Self-Regulating Plastic Synapses}},
author = {Giulioni, Massimiliano and Pannunzi, Mario and Badoni, Davide and Dante, Vittorio and Giudice, Paolo D.},
booktitle = {Neural Information Processing Systems},
year = {2007},
pages = {545-552},
url = {https://mlanthology.org/neurips/2007/giulioni2007neurips-configurable/}
}