A novel modification to backpropagation sample selection strategy

László Rédei, Hans Wallinga

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    1 Citation (Scopus)
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    Random sample selection method in backpropagation results in convergence on the error (root of mean squared error, RMSE) surface. These problems, which are caused by the extreme (worst-case) errors, can be solved by a different sample selection strategy. A sample selection strategy has been proposed, which provides lower maximal errors and a higher confidence level on the expense of slightly increased RMSE. Applications are presented in the field of spectroscopic ellipsometry (SE), a sensitive, non-destructive but indirect analytical technique. Demonstrative example shows feature common to simulated annealing in the sense of escaping local minima.
    Original languageEnglish
    Pages (from-to)233-236
    JournalNuclear instruments & methods in physics research. Section A : Accelerators, spectrometers, detectors and associated equipment
    Issue number1-2
    Publication statusPublished - 1997
    EventNew Computing Techniques in Physics Research V - AIHENP International Workshop 1996 - Lausanne, Switzerland
    Duration: 2 Sep 19966 Sep 1996
    Conference number: 5


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