This project uses my own mathematical model published in the journal Chaos. The model is called Spectral Forecast. The Spectral Forecast equation is a part of the Spectral Forecast model and it was initially used on matrices. It can also be used on other multidimensional mathematical objects. Here, a novel utility is demonstrated for signals by using the equation on vectors. This new use on 1-dimensional objects was published here. Combining-two-signals-in-JS-C-Py-PHP-VB-Pl-Rb-Java - is a demo implementation designed in eight different programming / scripting languages, namely C#, Python, VB6, Javascript, Perl, Ruby, Java and PHP. Each implementation is able to mix two signals / vectors (A and B) in arbitrary proportions. The signals are combined depending on a value d, called a distance. Distance d was arbitrary chosen (d=33) between zero and Max(d). Where Max(d) is defined from zero to the maximum value found above the two vectors that represent these signals.
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Paul A. Gagniuc et al. Spectral forecast: A general purpose prediction model as an alternative to classical neural networks. Chaos 30, 033119 (2020).
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Paul A. Gagniuc. Algorithms in Bioinformatics: Theory and Implementation. John Wiley & Sons, Hoboken, NJ, USA, 2021, ISBN: 9781119697961.