Combined compression and classification with learning vector quantization

John S. Baras*, Subhrakanti Dey

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    18 Citations (Scopus)

    Abstract

    Combined compression and classification problems are becoming increasingly important in many applications with large amounts of sensory data and large sets of classes. These applications range from automatic target recognition (ATR) to medical diagnosis, speech recognition, and fault detection and identification in manufacturing systems. In this paper, we develop and analyze a learning vector quantization (LVQ) based algorithm for combined compression and classification. We show convergence of the algorithm using the ODE method from stochastic approximation. We illustrate the performance of our algorithm with some examples.

    Original languageEnglish
    Pages (from-to)1911-1920
    Number of pages10
    JournalIEEE Transactions on Information Theory
    Volume45
    Issue number6
    DOIs
    Publication statusPublished - 1999

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