{"paper":{"title":"Energy Efficient and High Performance Current-Mode Neural Network Circuit using Memristors and Digitally Assisted Analog CMOS Neurons","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AR"],"primary_cat":"cs.ET","authors_text":"Aranya Goswamy, Kaushik Roy, Manny Jain, Mrigank Sharad, Sagar Kumashi, Siddharth Kumar Singh, Vikash Sehwag","submitted_at":"2015-11-29T20:27:15Z","abstract_excerpt":"Emerging nano-scale programmable Resistive-RAM (RRAM) has been identified as a promising technology for implementing brain-inspired computing hardware. Several neural network architectures, that essentially involve computation of scalar products between input data vectors and stored network weights can be efficiently implemented using high density cross-bar arrays of RRAM integrated with CMOS. In such a design, the CMOS interface may be responsible for providing input excitations and for processing the RRAM output. In order to achieve high energy efficiency along with high integration density "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1511.09085","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}