POPART: partial optical implementation of adaptive resonance theory 2

• Authors: J. S. Kane;M. J. Paquin
• Venue: IEEE Transactions on Neural Networks
• Year: 1993

Adaptive resonance architectures are neural nets that are capable of classifying arbitrary input patterns into stable category representations. A hybrid optoelectronic implementation utilizing an optical joint transform correlator is proposed and demonstrated. The resultant optoelectronic system is able to reduce the number of calculations compared to a strictly computer-based approach. The result is that, for larger images, the optoelectronic system is faster than the computer-based approach