Bipolar optical neural networks using ferroelectric liquid crystal devices

Abstract

Ferroelectric Liquid Crystal (FLC) electrooptic devices present some characteristics that make them attractive for the optical implementation of neural computers: high response speed and bistability, or intrinsic memory capability. Herein we will demonstrate how the electrooptic bistability of FLC materials can be used to implement bipolar optical neural networks, based on simple FLC cells that act as the neurons and as the interconnections among them.