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

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 d-rule learning algorithm to train the network to perform a number of functions toward the application area of telecommunication data switching.