POPART: partial optical implementation of adaptive resonance theory 2
Jonathan S. Kane, Marc J. Paquin · IEEE Transactions on Neural Networks · 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.