I have a metric to compare experiment results but I need vectors of equal size to do it.
The problem is that signal length can differ from one experiment to another so I need to reduce the signal dimension somehow.
What I tried/ideas:
- Calculate area under each signal. Result is vector of dimension $k$. The problem is that this method cannot differentiate signals with the same area.
- Split signal on $m$ bins and calculate an area in each bin. Result is a vector of dimension $k \times m$.
- Take Fourier series coefficients. Result is vector of dimension $(a+b)\times k$. The problem is that the spectrum is too large and Fourier cannot work nice (am I correct?)
- Some wavelet transforms (like Haar for example). But I don't understand how to do it correctly.
I will be grateful for advices or any method that can help me.