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 δ-rule learning algorithm to train the network to perform a number of functions toward the application area of telecommunication data switching.
© 1999 Optical Society of America
Full Article | PDF ArticleMore Like This
E. C. Mos, J. J. H. B. Schleipen, and H. de Waardt
Appl. Opt. 36(26) 6654-6663 (1997)
Neil Collings, Ali R. Pourzand, Fedor L. Vladimirov, Nina I. Pletneva, and Aleksander N. Chaika
Appl. Opt. 38(29) 6184-6189 (1999)
Richard G. Stearns
Appl. Opt. 31(29) 6230-6239 (1992)