Abstract

A programmable optoelectronic neural network architecture is presented that has been optimized to make routing decisions in both crossbar and banyan packet switch fabrics. Simulation has indicated excellent scalability in this particular application with only a minimal increase in decision time even when problem set size grows by an order of magnitude. Experimental results are presented that demonstrate a high tolerance to both noise and component inconsistencies. An assessment of system performance is made using the common metric of connections per second (CPS).

© 2003 Optical Society of America