Approximation of data using non-integer harmonics series

被引：2
|
作者：
Tenreiro Machado, J. A. [1 ]
Lopes, Antonio M. [2 ]
机构：
[1] Polytech Porto, Inst Engn, Dept Elect Engn, R Dr Antonio Bernardino de Almeida 431, P-4249015 Oporto, Portugal
[2] Univ Porto, Fac Engn, UISPA LAETA INEGI, Rua Dr Roberto Frias, P-4200465 Oporto, Portugal
来源：
NONLINEAR DYNAMICS | 2017年 / 89卷 / 04期
关键词：
Time series; Fourier series; Harmonics; Curve fitting; Forecasting; EMPIRICAL MODE DECOMPOSITION; WINDOWED FOURIER-TRANSFORM; PADE APPROXIMANTS; MACLAURIN SERIES; TIME; SIGNALS; CHAOS;
D O I：
10.1007/s11071-017-3629-4
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
This paper introduces a method for approximating real world data by means of non-integer harmonics series (NIHS). The NIHS terms are sinusoidal functions of arbitrary amplitude, frequency and phase shift that can be computed by direct numerical algorithms. Applications go from obtaining time derivatives up to forecasting future values. Three illustrative examples with the Dow Jones Industrial stock market index, the Europe Brent Spot Price FOB and the daily temperature records of New York city are studied. The results show the effectiveness of the NIHS when dealing with real world time data series.
引用
收藏
页码：2845 / 2854
页数：10
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