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This is an implementation designed in Perl. This implementation is able to mix two signals/vectors (A and B) in arbitrary proportions. This source code uses a novel mathematical model published in the journal Chaos. The model is called Spectral Forecast.

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Mix two signals in Perl

This is an implementation designed in Perl that is able to blend two signals in arbitrary proportions. This source code uses a novel mathematical model published in the journal Chaos. The model is called Spectral Forecast. The Mix-two-signals implementation is a demo that is able to mix two signals (A and B) in arbitrary proportions. Different cases can be seen, with two different waveform signals that are combined depending on a value d, called a distance. The value of d can be arbitrary chosen between zero and a value Max(d), which is defined as the maximum value found above the two vectors that represent these signals. In this specific case d = 33. The output is the M signal calculated from the two signals A and B, such as:

M = 15.37,35.12,51.12,57.17,47.89,43.08,60.35,67.91,63.72,48.03,33.99

The Spectral Forecast equation adapted to signals can be observed below:

screenshot

What can you expect from the code above? The effect of the above source code in the case of longer signals can be seen in a graphical form below:

screenshot

screenshot

screenshot

References

  • Paul A. Gagniuc et al. Spectral forecast: A general purpose prediction model as an alternative to classical neural networks. Chaos 30, 033119 (2020).

  • Paul A. Gagniuc. Algorithms in Bioinformatics: Theory and Implementation. John Wiley & Sons, Hoboken, NJ, USA, 2021, ISBN: 9781119697961.

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This is an implementation designed in Perl. This implementation is able to mix two signals/vectors (A and B) in arbitrary proportions. This source code uses a novel mathematical model published in the journal Chaos. The model is called Spectral Forecast.

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