Abstract
Pulse-to-pulse variability (PPV) is a vital nonideal effect in analog resistive memory, particularly for online training in emerging computing paradigms. The reported PPVs usually show two seemingly contradictory properties: large PPV amplitude between neighboring write pulses but statistically stable switching curves. In this article, a new insight is proposed to unambiguously decouple PPV into two independent components: variability and curve fluctuation. Furthermore, a phenomenological modeling and parameter extraction method is proposed to capture this characteristic. The proposed model can facilitate the exploration of PPV impact on neural network accuracy for online training.
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.
