Feature engineering
We will use several libraries specific to signal processing to generate most of the features. From SciPy (Python scientific library), we are using a few functions from the signal module. The Hann function returns a Hann window, which modifies the signal to smooth the values at the end of the sampled signal to 0 (uses a cosine “bell” function). The Hilbert function computes the analytic signal, using the Hilbert transform. The Hilbert transform is a mathematical technique used in signal processing, with a property that shifts the phase of the original signal by 90 degrees.
Other library functions used are from numpy: Fast Fourier Transform (FFT), mean, min, max, std (standard deviation), abs (absolute value), diff (the difference between two successive values in the signal), and quantile (where a sample is divided into equal-sized, adjacent groups). We are also using a few statistical functions that are available from pandas: mad (median absolute...
