breaking the input signal into segments while calculating DFT Im reading a book about DSP and there is an example about investigating the sound that travel through the ocean. The sound was recorded as the time-domain signal and they tried to analyze it in frequency domain. 

The input signal was broke up into 256 point segments. Each of these segments is multiplied by the Hamming window, then run through a 256 point DFT. The resulting frequency spectra are then averaged to form a single 129 point frequency spectrum. Please take a look at the figure  



I don't understand:


How they break up the input signal into 256 segments?
How each segment was multiplied with the Hamming window?
How they calculate 256 DFT points?
How the frequency spectra was averaged?
How they break up the input signal into 256 segments?


This is usually done by a sliding a window of a given width (here 256). Depending on the step-size this results in overlapping (if smaller than 256) or non-overlapping (if equal or larger than 256) data segments.


  How each segment was multiplied with the Hamming window?


Usually, by an element-wise multiplication.


  How they calculate 256 DFT points?


The number of DFT points is, if I am not mistaken, determined by the length of the input signal.


  How the frequency spectra was averaged?


All resulting spectra were summed up and divided by the number of spectra.