# Getting SNR of reconstructed signal in MATLAB

I am trying to run code to compare the efficiency of various basic sampling methods such as ideal sampling, natural sampling and so on. I want to then use average power to see how accurate the reconstructions are. From my understanding, there should be some additional power in my reconstructed signal that would represent some additive noise. Is that a fair estimate? My goal was to then divide original signal power by what I assumed is additive noise to obtain SNR. Is that fair? My problem is that my original signal has a greater power when I use the formula:

((norm(x)^2)/length(x))-((norm(x_re)^2)/length(x_re))



I get a positive x is my message signal and x_delta is my reconstructed signal. If this is positve, is it attenuation? Is there any way in which I can use it? If not how else could I find a required SNR