Shift-invariant interpattern association neural network

Chii Maw Uang, Shizhuo Yin, P. Andres, Wade Reeser, Francis T.S. Yu

    Research output: Contribution to journalArticlepeer-review

    1 Scopus citations

    Abstract

    A shift-invariant neural network that uses the translation-invariant property of the modulus Fourier spectra with the heteroassociation interpattern association memory is proposed. A binary encoding of a spectral sampling of the training set is used to preserve the main features. Computer simulations and experimental demonstrations are provided that show the shift-invariant property of the proposed optical neural network.

    Original languageEnglish (US)
    Pages (from-to)2147-2151
    Number of pages5
    JournalApplied Optics
    Volume33
    Issue number11
    DOIs
    StatePublished - Apr 10 1994

    All Science Journal Classification (ASJC) codes

    • Atomic and Molecular Physics, and Optics
    • Engineering (miscellaneous)
    • Electrical and Electronic Engineering

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