they use the specgram function.  I have looked at this before but I cannot understand what the NFFT parameter is?

I have also used the spectrum function with some success, but I find that the results are not very accurate.  I have created a sin wave at 440Hz and when I analyze it, the graph plot is close but sometimes it is almost 50- 100 Hz off.  Does anyone know if its something I am doing or maybe the sin wave tone is only approx. 440Hz when I create it?

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they use the specgram function.  I have looked at this before but I cannot understand what the NFFT parameter is?

I believe it is the window size the fft is performed on. When you want to plot frequency graphs over time, you only want to analyze a small portion of samples at a time. NFFT is probably the size of this window. It is a tradeoff between time precision and frequency precision. Small numbers mean high time resolution while high numbers mean high frequency resolution.

It's a good idea to use powers of two because of the way the fast discrete fourier transform works.

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I have also used the spectrum function with some success, but I find that the results are not very accurate.  I have created a sin wave at 440Hz and when I analyze it, the graph plot is close but sometimes it is almost 50- 100 Hz off.  Does anyone know if its something I am doing or maybe the sin wave tone is only approx. 440Hz when I create it?

Maybe the window is too short?

With NFFT = 256 you look at 256 samples at a time. If the data is sampled at 44100 samples/second that would be ca 0.0058 seconds of sound. So the lowest frequency you can discriminate is ca. 172Hz (1/0.0058). [span style='font-size:8pt;line-height:100%']edit:[/span] The discrete frequencies you will see are multiples of that base frequency. 172.27, 344.53, 516.80, 689.06. As you can see the frequency resolution isn't good enough.

[span style='font-size:8pt;line-height:100%']Old text: The next frequency bin would be at 344Hz, the next at 689Hz.[/span]

Someone please verify this! It's been a while.

Thanks for your reply,
I'll try what you suggest.  Time is not important (if I must give one up for the other), but I would like to know the amplitude of each frequency(even if it is just by comparing it to the other frequencies present in the sound.).  How can this be done?

Also, why is it that one cannot be accurate in both freq. and time?

And when you say that freq. and loudness is logarithmic and Matlab plots are not: Do you mean that I would have to scale the plots logarithmically and not use the default setting?

window_length=4096;
freq_my_tone=fft(my_tone(1:window_length).*hanning(window_length));
frequency_scale=(1:window_length/2)*fs/window_length;
semilogx(frequency_scale,20*log10(abs(freq_my_tone(1:window_length/2))))
axis([20 20000 -20 80])
xlabel('frequency / Hz')
ylabel('amplitude / dB')