An improved novelty criterion for resource allocating networks

Alan McLachlan

    Research output: Chapter in Book/Report/Conference proceedingChapter

    Abstract

    Online model order complexity estimation remains one of the key problems in neural network research. The problem is further exacerbated in situations where the underlying system generator is non-stationary. In this paper, we introduce a novelty criterion for resource allocating networks (RANs) which is capable of being applied to both stationary and slowly varying non-stationary problems. The deficiencies of existing novelty criteria are discussed and the relative performances are demonstrated on two real-world problems : electricity load forecasting and exchange rate prediction.
    Original languageEnglish
    Title of host publicationFifth International Conference on Artificial Neural Networks
    PublisherIEEE
    Pages48-52
    Number of pages5
    Volume440
    ISBN (Print)0852966903
    Publication statusPublished - 7 Jul 1997
    EventFifth International Conference on Artificial Neural Networks -
    Duration: 7 Jul 19977 Jul 1997

    Publication series

    NameConference publication
    PublisherInstitute of Electrical and Electronics Engineers (IEEE)
    Volume440

    Conference

    ConferenceFifth International Conference on Artificial Neural Networks
    Period7/07/977/07/97

    Bibliographical note

    ©1997 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

    Keywords

    • feedforward neural nets
    • electricity load forecasting
    • exchange rate prediction
    • extended Kalman filter training
    • algorithm
    • network growth
    • network growth prescription
    • nonstationary real-world problems
    • novelty criterion
    • radial basis function network resource allocation
    • signal processing theory
    • slowly varying nonstationary environment

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  • Cite this

    McLachlan, A. (1997). An improved novelty criterion for resource allocating networks. In Fifth International Conference on Artificial Neural Networks (Vol. 440, pp. 48-52). (Conference publication; Vol. 440). IEEE.