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FFT Windowing
post Jun 5 2003, 17:42
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I am in the process of trying to understand FFT analysis as it pertains to audio, and I have come across the concept of FFT windowing. Am I understanding it correctly that the main use of FFT windowing is to get better results in the frequency domain (ex. minimizing Gibbs Phenomenon) ?

It seems that one of the most common window functions used is the Hamming window. If I want to use the Hamming window do I just apply and upward slope from the first sample in my data chunk to the center sample and a downward slope from the center sample to the last sample? (This is what the graph in front of me shows) Or is there an explicit mathematical method I am not aware of?

Edit: Is the Hamming window good for complex signals too? (the example I read about had only one frequency involved)

This post has been edited by RiskyP: Jun 5 2003, 17:43
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post Jun 5 2003, 21:19
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A frequency bin is simply an FFT output value which represents a specific frequency. If you perform, for instance, a 16-point FFT, you're computing 8 frequency components equally spaced between DC and Nyquist (Fs/2). You now have an 8-frequency spectrum analysis of the signal. Frequencies in the source data that fall outside the 8 frequency bins or slots bleed onto adjacent bins. In order to reduce the bleeding and improve resolution, windowing of the source data is used.



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