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Proceedings Paper

Liquid crystal cells and optical fibers in neural network implementation
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Paper Abstract

Optical binary computer may be as easy to operate as parallel system. For such configuration Boolean logic is not very convenient and therefore neural networks should be introduced. In works leading to the paper we used liquid crystal cells as a standard system of liquid crystalline layer between to conducting electrodes in 'sandwich' geometry. We have used 25 micrometers display cells filled with nematic 6CHBT working on 'twisted nematic' effect. Based on such elements a mode of a simple Hopfield network was set up. More advanced experiments were carried out on a model of neurone with supervised learning. The model consists of four laser diodes pigtailed to the multimode optical fibers with 50 micrometers core diameter. The directional couplers help to control the level of input optical power. Four liquid crystal cells allow to change the transmission level according to superivised learning requirements. All the signals were detected by one photodiode. The presented results of experiments are in excellent agreement with theoretical predictions. An additional study was done to check the possibility to build up a linear neural network with Grossberg layer, a neural network with Kohonen layer, and a counter propagation network with two layers of neurones. We have proved that such models may be set up based on simple liquid crystals cells and optical fiber networks.

Paper Details

Date Published: 2 August 1995
PDF: 6 pages
Proc. SPIE 2372, Liquid Crystals: Materials Science and Applications, (2 August 1995); doi: 10.1117/12.215564
Show Author Affiliations
Andrzej W. Domanski, Warsaw Univ. of Technology (Poland)
Ryszard Buczynski, Warsaw Univ. of Technology (Poland)
Marek Wojciech Sierakowski, Warsaw Univ. of Technology (Poland)


Published in SPIE Proceedings Vol. 2372:
Liquid Crystals: Materials Science and Applications
Jozef Zmija, Editor(s)

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