Rectifying resistive memory devices as dynamic complementary artificial synapses

• Main Author: Berco, Dan
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2019
• Subjects: Brain Inspired Computing; Artificial Neural Networks; DRNTU::Engineering::Electrical and electronic engineering
• Online Access: https://hdl.handle.net/10356/103559; http://hdl.handle.net/10220/47332
• Institution: Nanyang Technological University

Brain inspired computing is a pioneering computational method gaining momentum in recent years. Within this scheme, artificial neural networks are implemented using two main approaches: software algorithms and designated hardware architectures. However, while software implementations show remarkable...