Hash-coding in CMAC neural networks

Zi Qin Wang, Jeffrey L. Schiano, Mark Ginsberg

    Research output: Contribution to conferencePaperpeer-review

    27 Scopus citations

    Abstract

    Hash-coding is used in CMAC neural networks to reduce the required memory, thereby making the CMAC practical to implement. In this paper the original motivation and rationale for using hash-coding in CMAC [1] are questioned and it is shown that, contrary to the traditional believe, that hash-coding is unable to enhance CMAC's approximation ability. A comparison between the CMAC performance obtained with two popular hash-coding methods is given.

    Original languageEnglish (US)
    Pages1698-1703
    Number of pages6
    StatePublished - Jan 1 1996
    EventProceedings of the 1996 IEEE International Conference on Neural Networks, ICNN. Part 1 (of 4) - Washington, DC, USA
    Duration: Jun 3 1996Jun 6 1996

    Other

    OtherProceedings of the 1996 IEEE International Conference on Neural Networks, ICNN. Part 1 (of 4)
    CityWashington, DC, USA
    Period6/3/966/6/96

    All Science Journal Classification (ASJC) codes

    • Software

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