Using genetic algorithms for an optical thin-film learning model
Li, Xiaodong; Purvis, Martin
A novel connectionist architecture based on an optical thin-film multilayer model (OTFM) is described. The architecture is explored as an alternative to the widely used neuron-inspired models, with the thin-film thicknesses serving as adjustable ‘weights’ for the computation. The use of genetic algorithms for training the thin-film model, along with experimental results on the parity problem and the iris data classification are presented.
Publisher: University of Otago
Series number: 96/20
Research Type: Discussion Paper
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