Accession Number : ADA587910


Title :   Memristor-Based Synapse Design and Training Scheme for Neuromorphic Computing Architecture


Descriptive Note : Conference paper


Corporate Author : AIR FORCE RESEARCH LAB ROME NY INFORMATION DIRECTORATE


Personal Author(s) : Wang, Hui ; Li, Hai H ; Pino, Robinson


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a587910.pdf


Report Date : Jun 2012


Pagination or Media Count : 6


Abstract : Memristors have been rediscovered recently and then gained increasing attentions. Their unique properties, such as high density, nonvolatility, and recording historic behavior of current (or voltage) profile, have inspired the creation of memristor-based neuromorphic computing architecture. Rather than the existing crossbar-based neuron network designs, we focus on memristor-based synapse and the corresponding training circuit to mimic the real biological system. In this paper, first, the basic synapse design is presented. On top of it, we will discuss the training sharing scheme and explore design implication on multi-synapse neuron system. Energy saving method such as self-training is also investigated.


Descriptors :   *COMPUTER ARCHITECTURE , BIOMIMETICS , ENERGY CONSERVATION , GATES(CIRCUITS) , NERVE CELLS


Subject Categories : Computer Hardware


Distribution Statement : APPROVED FOR PUBLIC RELEASE