1 June 1991 Liquid-crystal television optical neural network: architecture, design, and models
Author Affiliations +
An adaptive optical neural network (ONN) using inexpensive pocket-size liquid crystal televisions (LCTVs) and containing 8 X 8 equals 64 neurons was constructed by a group of graduate students in the Electro-Optics Laboratory at The Pennsylvania State University. By the limited resolution of the LCTV, the current optical architecture can be easily extended to 16 X 20 equals 320 neurons. The major advantages of this LCTV architecture as compared with other reported ONNs are low cost and the flexibility to operate. To test the performance, several neural network models are implemented, in which are interpattern association, hetero- association, and unsupervised learning algorithm. The system design considerations and experimental demonstrations of the neural network models are given.
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Francis T. S. Yu, "Liquid-crystal television optical neural network: architecture, design, and models", Proc. SPIE 1455, Liquid-Crystal Devices and Materials, (1 June 1991); doi: 10.1117/12.44688; https://doi.org/10.1117/12.44688

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