STFT computational burden I have a signal with length of $N$.
The sampling frequency is $f_s$.
Window size is $w$
The noverlap size is set to $m$.
And $nfft$ is selected for frequency resolutions.


I am running a STFT with matlab spectrogram function.  

[S,F,T,P]=spectrogram(x,window,noverlap,nfft,fs)  



what is the effect of nfft , $f_s$ and  noverlap on STFT
computational burden?
what is computation complexity of STFT with these parameters size?
{in term of big O() }


Note: The FFT computational complexity for a signal with length of $N$ is $Nlog(N)$
The number of FFTs is roughly N/(w-m). An fft costs you nfft*log2(nfft) so the total is proportional to N/(w-m)*nfft*log2(nfft). 

A typical application would make nfft = w and m = w/2, so this would come out to be proportional to N*log2(nfft). So it's proportional to the length or you data set (obviously) and the log of the FFT size.