Energy using Hanning window I am a newbie in signal processing. I am testing the Hanning window on a signal. Obviously doing this window also means cut some energy of the signal, and when I do the DFT, the 0 frequency is not equivalent anymore to the average of the time history. Do you usually solve in some way this problem?
Can someone suggest papers or books where noise-reducing strategies for the FT of a signal are investigated? I just don't know how to start, an online search didn't give me more than basic definition (so please don't send me the Wikipedia definition of the tapering window)

Best
I suspect you are talking about the Hann window, after Julius von Hann, and Blackman &amp; Tukey. Of course, a non-constant window may induce energy variations, either used as a weighted average, or a convolutional filter. This can be compensated in several ways:


by normalizing the window amplitudes
by separating tipme-portions, or signal components, like removing the mean or low-frequencies before doing the processing
by modelling the signal and applying model-based corrections. 


More would be needed on your signal to provide more precise answers. R. Lyons on a diagram on page xviii of his book Understanding Digital Signal Processing highlights the importance of windows.