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Proceedings Paper

Performance comparison of the Prophecy (forecasting) Algorithm in FFT form for unseen feature and time-series prediction
Author(s): Holger Jaenisch; James Handley
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Paper Abstract

We introduce a generalized numerical prediction and forecasting algorithm. We have previously published it for malware byte sequence feature prediction and generalized distribution modeling for disparate test article analysis. We show how non-trivial non-periodic extrapolation of a numerical sequence (forecast and backcast) from the starting data is possible. Our ancestor-progeny prediction can yield new options for evolutionary programming. Our equations enable analytical integrals and derivatives to any order. Interpolation is controllable from smooth continuous to fractal structure estimation. We show how our generalized trigonometric polynomial can be derived using a Fourier transform.

Paper Details

Date Published: 6 June 2013
PDF: 20 pages
Proc. SPIE 8757, Cyber Sensing 2013, 87570F (6 June 2013); doi: 10.1117/12.2015417
Show Author Affiliations
Holger Jaenisch, Licht Strahl Engineering, Inc. (United States)
Johns Hopkins Univ. (United States)
James Handley, Licht Strahl Engineering, Inc. (United States)


Published in SPIE Proceedings Vol. 8757:
Cyber Sensing 2013
Igor V. Ternovskiy; Peter Chin, Editor(s)

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