If I'm analyzing a signal in the frequency domain, I know about the well known Nyquist criteria that the sample frequency must be > 2x of the highest component present in the signal.
However, there are very few references related to the lowest frequency I can analyze. This problem comes up in a lot of natural data where we have limited windows of observation because the instruments to do so were only invented or in wide spread use in the last 50-100 years, and natural cycles can be decades, centuries, or longer.
One would think that you could analyze a component where at least one period was in the sample window, but I find because of required windowing to prevent edge effects that the signal often disappears (it depends on the phase). I then thought it was a mirror of Nyquist and I could resolve any signal with at least 2 periods in a window, but actual analysis shows that to not be true when there's a another overlying signal whose period is similar.
I found through experiment that I needed at least 5 periods to resolve a signal where there's another signal near the same frequency.
Is there a formal way of representing this problem or a definitive reference I can use?
Would the same issue apply to wavelet analysis in the same manner?