Abstract
The mathematical relationships between the operating voltages and the conductance of resistance random-access memory (RRAM) are found based on the statistical measurements of the 1-transistor 1-RRAM (1T1R) array. According to the corresponding relationships, a one-shot operation scheme without verification after programming is proposed for weight updating of RRAM-based neural networks. The proposed operation scheme enables parallel column-by-column SET and row-by-row RESET, which achieves fast and accurate conductance modulation in the 1T1R array. By utilizing the one-shot scheme for weight updating of the deep-Q network, the training efficiency improves 40 times compared with the incremental step pulse programming (ISPP) scheme.
Sign-in/Register to access full text options 
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.
