POPART: partial optical implementation of adaptive resonance theory 2

Author(s): Kane, J.S. | Paquin, M.J. |

Year: 1993

Citation: IEEE Transactions on Neural Networks, vol.4, no.4, pp.695-702

Abstract: 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.

Topics: Image Analysis, Applications: Character Recognition, Models: ART 2-A,

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