From Memory in our Brain to Emerging Resistive Memories in Neuromorphic Systems

Abstract

In this work, we will focus on the role that new nonvolatile resistive memory technologies (as OxRAM and CBRAM) can play in emerging fields of application, such as neuromorphic circuits, to save energy and increase performance. We will present large-scale energy efficient neuromorphic systems based on ReRAM as stochastic-binary synapses. Prototype applications such as complex visual- and auditory-pattern extraction will be discussed using feedforward spiking neural networks. A parallel will be drawn between these systems and human memory, as recent discoveries on the human brain and cognitive processes may bring benefits and open new perspectives for intelligent data processing.