simple FFT/IFFT filter vs. e.g. butterworth filtering

Discussion in 'Programmer's Corner' started by Annemieke, May 20, 2014.

  1. Annemieke

    Thread Starter New Member

    May 20, 2014
    I am currently working on functional connectivity analysis of EEG, and need to bandpass filter my data into different frequency bands (Delta, Theta, Alpha and Beta). An important thing is that the filter doesn't cause phase distortion. I know a butterworth filter and processing the data in both the forward and reverse directions (e.g. with filtfilt in Matlab) is a good approach, however I was still wondering about the simple FFT/IFFT filtering approach. What are the exact disadvantages of this method? Does this method cause phase distortions? What are 'edge effects' that occur with this method?
  2. Papabravo


    Feb 24, 2006
    I'm not sure I understand the idea behind using an FFT for filtering. It transforms the time domain information into the frequency domain so you can see all the frequency components of a given signal. It is important to have an analog anti-aliasing filter to limit the bandwidth of the input signal so that frequency components that exceed twice the sampling frequency will not be folded back into the baseband.

    Also could you tell us what your understanding of "phase distortion" is. Does a phase shift as a function of frequency count as "phase distortion"?
  3. t06afre

    AAC Fanatic!

    May 11, 2009
    Any analog or digital filter will cause a phase shift. What do you want to get out of your analysis. That is an important question that we miss a answer to.