Abstract
Stochastic spiking Neural Networks (SNN) is a new neural modeling oriented to include the intrinsic stochastic processes present in the brain. One of the main advantages of this kind of modeling is that they can be easily implemented in a digital circuit, thus taking advantage of this mature technology. In this paper we propose a digital design for stochastic spiking neurons oriented to high-density hardware implementation. We compare the proposal with other neural models, comparing in terms of speed, area and precision. As is shown, the circuit proposal is able to provide competitive results when comparing with other works present in the literature.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
