This Javascript 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. Signal processing with Spectral Forecast - is a demo application designed in Javascript, 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. This distance 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. Note that the construction and theory behind the chart of this application can be found here.
Live demo: https://gagniuc.github.io/Signal-processing-with-Spectral-Forecast/
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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.