Publication
An FPGA-based model suitable for evolution and development of spiking neural networks
AbstractWe propose a digital neuron model suitable for evolving and growing heterogeneous spiking neural networks on FPGAs using a piecewise linear approximation of the Quadratic Integrate and Fire (QIF) model. A network of 161 neurons and 1610 synapses with 4210 times realtime neuron simulation speed was simulated and synthesized for a Virtex-5 chip.
Download publicationAssociated Researchers
Related Resources
See what’s new.
2022
Communicating Natural Programs to Humans and MachinesThe Abstraction and Reasoning Corpus (ARC) is a set of procedural…
2020
Contrastive Multi-View Representation Learning on GraphsWe introduce a self-supervised approach for learning node and graph…
Get in touch
Something pique your interest? Get in touch if you’d like to learn more about Autodesk Research, our projects, people, and potential collaboration opportunities.
Contact us