Performance comparison of the Prophecy (forecasting) Algorithm in FFT form for unseen feature and time-series prediction

Holger Jaenisch; James Handley

doi:10.1117/12.2015417

6 June 2013 Performance comparison of the Prophecy (forecasting) Algorithm in FFT form for unseen feature and time-series prediction

Holger Jaenisch, James Handley

Author Affiliations +

Proceedings Volume 8757, Cyber Sensing 2013; 87570F (2013) https://doi.org/10.1117/12.2015417
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

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.

Citation Download Citation

Holger Jaenisch and James Handley "Performance comparison of the Prophecy (forecasting) Algorithm in FFT form for unseen feature and time-series prediction", Proc. SPIE 8757, Cyber Sensing 2013, 87570F (6 June 2013); https://doi.org/10.1117/12.2015417

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