1 July 1992 Optical winner-take-all neural network using electron trapping materials
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Exemplar-based neural net classifiers enjoy extremely rapid learning procedures and are particularly suitable for analog optical hardware implementations. The winner-take-all (WTA) network is a key component in exemplar-based neural net classifiers as well as in optical competitive learning architectures. In this paper, we present an optical WTA network based on novel electron trapping (ET) materials. The mathematical model has been modified for the optical implementation. All the neuron operations required by the WTA network such as self- excitation, lateral inhibition and thresholding, are performed by a single ET device.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiangyang Yang, William M. Seiderman, Ravindra A. Athale, and Michael Astor "Optical winner-take-all neural network using electron trapping materials", Proc. SPIE 1701, Optical Pattern Recognition III, (1 July 1992); doi: 10.1117/12.138338; https://doi.org/10.1117/12.138338

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