NDLI: Prediction of the CATS benchmark exploiting time-reversal symmetry

Content Provider	IEEE Xplore Digital Library
Author	Verdes, P.F. Granitto, P.M. Szeliga, M.I. Rebola, A. Ceccatto, H.A.
Copyright Year	2004
Description	Author affiliation: Inst. fur Umweltphysik, Heidelberg Univ., Germany (Verdes, P.F.)
Abstract	We present a possible strategy for filling the missing data of the CATS benchmark time series prediction competition. Our approach builds upon an appropriate embedding of this time series and the use of bagging of multilayer perceptrons (MLPs). We exploit time-reversal symmetry for prediction within the first four gaps, linking the missing state to symmetrically-located information both in the past and future. One-shot forecasting is then performed for each missing value from distant-enough delays. The suitability of the proposed embedding is assessed empirically by t-testing the goodness-of-fit of models built in symmetric versus asymmetric input spaces. Since this approach cannot be pursued for forecasting the continuation of this time series, in the right end we perform standard, non-iterated forward predictions. Expected error levels are provided according to the performance on test data.
Starting Page	1631
Ending Page	1634
File Size	297792
Page Count	4
File Format	PDF
ISBN	0780383591
ISSN	10987576
DOI	10.1109/IJCNN.2004.1380204
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-07-25
Publisher Place	Hungary
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cats Data analysis Filling Bagging Multilayer perceptrons Joining processes Delay Benchmark testing Phase estimation Phase noise
Content Type	Text
Resource Type	Article

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