Loop mirror laser neural network with a fast liquid-crystal display

Appl Opt. 1999 Jul 10;38(20):4359-68. doi: 10.1364/ao.38.004359.

Abstract

In our laser neural network (LNN) all-optical threshold action is obtained by application of controlled optical feedback to a laser diode. Here an extended experimental LNN is presented with as many as 32 neurons and 12 inputs. In the setup we use a fast liquid-crystal display to implement an optical matrix vector multiplier. This display, based on ferroelectric liquid-crystal material, enables us to present 125 training examples/s to the LNN. To maximize the optical feedback efficiency of the setup, a loop mirror is introduced. We use a delta-rule learning algorithm to train the network to perform a number of functions toward the application area of telecommunication data switching.