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A super‐resolution algorithm for spectral estimation and time series extrapolation
Author(s) -
Moutter S. P.,
Bodger P. S.,
Gough P. T.
Publication year - 1986
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.3980050304
Subject(s) - extrapolation , series (stratigraphy) , algorithm , computer science , time series , time domain , field (mathematics) , term (time) , mathematics , statistics , machine learning , quantum mechanics , pure mathematics , computer vision , biology , paleontology , physics
Recent developments in the signal processing field of electrical engineering have resulted in several frequency domain methods of extrapolating a time series. Insight gained in testing one such method, the Papoulis algorithm, has been used to suggest modifications which greatly improve its performance under most operating conditions where real data are concerned. The modified Papoulis method thus developed has been applied to electricity load forecasting over the short and medium term, as well as to world economic and energy data, to assess the cyclic structure present in each series about a trend.