INCOMPLETELY DETERMINED MODEL FOR APPROXIMATING FUNCTIONS FROM EXPERIMENTAL DATA.

Viktor Brailovsky*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The problem of approximating a function from its samples for an incompletely determined model (for example, if a system of approximating functions is not completely known) is discussed and some properties of the approximation are found. The case with defects in the samples in the form of contamination or missing data is considered. The problem of how to select the functions to be used in the model is studied under different conditions. Some qualitative effects caused by defects in the samples are ascertained. This is only a summary of a paper to be published in full elsewhere.

Original languageEnglish
Title of host publicationProceedings - International Conference on Pattern Recognition
PublisherIEEE
Pages1263-1265
Number of pages3
ISBN (Print)0818605456
StatePublished - 1984

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume2

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