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dc.contributor.authorKaikhah, Khosrowen_US
dc.contributor.authorLoochan, F.en_US
dc.date.accessioned2012-02-24T10:17:49Z
dc.date.available2012-02-24T10:17:49Z
dc.date.issued2001-03-01en_US
dc.identifier.urihttps://digital.library.txstate.edu/handle/10877/3811
dc.description.abstractWhile numerous artificial neural network (ANN) models have been electronically implemented and simulated by conventional computers, optical technology provides a far superior mechanism for the implementation of large-scale ANNs. The properties of light make it an ideal carrier of data signals. With optics, very large and high speed neural network architectures are possible. Because light is a predictable phenomenon, it can be described mathematically and its behavior can be simulated by conventional computers. A hologram is in essence a capture of the light field at a particular moment in time and space. Later, the hologram can be used to reconstruct the three dimensional light field carrying optical data. This makes a hologram an ideal medium for capturing, storing, and transmitting data in optical computers, such as optical neural networks (ONNs). Holograms can be created using conventional methods, but they can also be computer generated. In this paper, we will present an overview of optical neural networks, with emphasis on the holographic neural networks. We will take a look at the mathematical basis of holography in terms of the Fresnel Zone Plate and how it can be utilized in making computer generated holograms (CGHs). Finally, we will present various methods of CGH implementation in a two layer holographic ONN.en_US
dc.formatText
dc.format.extent26 pages
dc.format.medium1 file (.pdf)
dc.language.isoen_US
dc.publisherKluwer Academic Publishers
dc.sourceThe International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-solving Technologies, March/April 2001. Dordrecht, Netherlands: Kluwer Academic Publishers. Vol. 14, No. 2, pp. 145-160.
dc.subjectNeural networksen_US
dc.subjectOptical hologramsen_US
dc.titleComputer Generated Holograms for Optical Neural Networksen_US
txstate.documenttypeArticle
txstate.departmentComputer Science


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