The easiest way to smooth a signal is by moving window average.
A more advanced way is to use a Savitzky-Golay filter. From wikipedia:
The main advantage of this approach is that it tends to preserve features of the distribution such as relative maxima, minima and width, which are usually 'flattened' by other adjacent averaging techniques (like moving averages, for example).
There is also a whole range of window functions. As I understand this: any finite filter wil cause spectral leakage, but the moving window average is the worst. E.g. a Gaussian window is better in this respect.
Is flattening and spectral leakage the same?
When should one use Savitzky-Golay and when should one use Gauss, Hann, Hamming etc?
Thanks in advance for any answers!