For de$-$noising an EEG, we need to study the power spectrum of a brainwave. The power spectrum of a brainwave, from an electroencephalogram $($EEG$)$ is shown below. Note: "Electroencephalography is a method to record an electrogram of the spontaneous electrical activity of the brain. The biosignals detected by EEG have been shown to represent the postsynaptic potentials of pyramidal neurons in the neocortex and allocortex". Quoted from Wikipedia"

Quoted graphs from, Brain$-$Computer Interface, reference.

Use up to $50$ points for the three languages, create and fit a regression model using the Newton Gregory $($Polynomials a $5^{th})$ order polynomial models for frequency ranges $(40$ and to $50)$ for both rad$/$second power spectrum for both EEG. Write your own code $($any coding platform: $c++,$ matlab, or python$),$ to verify the models and to verify your results. I prefer python coding if possible. $(5$ marks$).$

Use up to $50$ points for the three languages, create and fit a regression model using the LSE $-$ Least Square Error algorithm $-($Polynomials a $5^{th})$ order polynomial models for frequency ranges $(40$ and to $50)$ for both rad$/$second power spectrum for both EEG. Write your own code $($any coding platform: $c++,$ matlab, or python$),$ to verify the models and to verify your results. I prefer python coding if possible. $(5$ marks$).$