Abstract
Resistance random access memories (RRAM) or memristors with an analog change of conductance are widely explored as an artificial synapse, e.g., Pr0.7Ca0.3MnO3 (PCMO) RRAM-based synapses. In addition to synapses, scaled neurons are essential to enable a neuromorphic hardware. In this letter, we propose a PCMO RRAM for integrate and fire (IF) neuron. The analog conductance increase during SET process enables integration function. Upon exceeding a conductance threshold (i.e., fire) during a READ operation, a hard RESET is performed to reduce the conductance. The SET, READ, and RESET are performed in different phases of a clock to enable a PCMO for IF neuron. The availability of a non-volatile PCMO-based synapse makes PCMO for IF neuron attractive. Finally, PCMO-based neuron in spiking neural network yields software-equivalent classification accuracy as demonstrated on standard Fischer’s Iris flower data set.
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.
