Content-addressable polychromatic neural net using a specially doped LiNbO3 photorefractive crystal

Francis T. Yu, Shizhuo Yin, Chii Maw Uang

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    In this paper, a polychromatic neural net using a specially doped LiNbO3 photorefractive crystal is presented. This neural net is a two-level high-content addressable memory. The first level is a polychromatic Hamming net for color image classification, and the second level is a mapping net, based on a photorefractive crystal associative memory. The major advantage of this neural net must be the large storage capacity and it requires fewer interconnection links. Experimental demonstrations are provided, in which we have shown that the proposed neural net is consistent with the theoretical model.

    Original languageEnglish (US)
    Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
    EditorsDavid P. Casasent
    PublisherPubl by Society of Photo-Optical Instrumentation Engineers
    Pages431-441
    Number of pages11
    Volume1959
    ISBN (Print)0819411957
    StatePublished - Dec 1 1993
    EventOptical Pattern Recognition IV - Orlando, FL, USA
    Duration: Apr 13 1993Apr 14 1993

    Other

    OtherOptical Pattern Recognition IV
    CityOrlando, FL, USA
    Period4/13/934/14/93

    All Science Journal Classification (ASJC) codes

    • Electronic, Optical and Magnetic Materials
    • Condensed Matter Physics
    • Computer Science Applications
    • Applied Mathematics
    • Electrical and Electronic Engineering

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