Shift- and rotation-invariant interpattern heteroassociation (IHA) model

Chii Maw Uang, Shizhuo Yin, Guowen Lu, Francis T.S. Yu

    Research output: Contribution to journalArticle

    4 Scopus citations

    Abstract

    A shift- and rotation-invariant netral work using an interpattern heteroassociation (IHA) model is illustrated. The shift- and rotation-invariant properties are achived by using a set of binarized-encoded circular harmonic expansion (CHE) functions in the Fourier domain as the network training set. Because of the shift-invariant and symmetric properties of the modulus of Fourier spectrum, the problem of locating the center of the CHE functions can be avoided. Computer simulations and experimental demonstrations that demonstrate the shift- and the rotation-invariant properties of the proposed IHA neural net are provided.

    Original languageEnglish (US)
    Pages (from-to)285-292
    Number of pages8
    JournalOptics Communications
    Volume104
    Issue number4-6
    DOIs
    StatePublished - Jan 1 1994

    All Science Journal Classification (ASJC) codes

    • Electronic, Optical and Magnetic Materials
    • Atomic and Molecular Physics, and Optics
    • Physical and Theoretical Chemistry
    • Electrical and Electronic Engineering

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