MATLAB: How to design a FIR filter with Parks-McCllean algorithm

fir filterparks-mccllean algorithm

frequency range is 39∼53MHz, pass-band peak to peak is 2.5dB, stop-band attenuation is 40dB, the filter order 65 (to achieve a steep transition zone), by constrained equiripple filter, with Parks-McCllean algorithm

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Use the Signal Processing Toolbox firpm (link) function and its friends (linked to in and at the end of the page).

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MATLAB: Fir and iir filtering

You have to know your filter specifications. If you do, you can do both with fdesign.lowpass and fdesign.highpass

fdesign.lowpass and fdesign.highpass have different specification strings which support different filter designs.

The default string 'Fp,Fst,Ap,Ast' supports both FIR and IIR designs.

Here is an example:

Design a lowpass filter with a passband frequency of 1 kHz, a stopband frequency of 1.5 kHz, passband ripple of 0.5 dB, and stopband attenuation of 40 dB. The sampling frequency is 20 kHz

   d = fdesign.lowpass('Fp,Fst,Ap,Ast',1e3,1.5e3,0.5,40,20e3);
   designmethods(d)  %shows which designs are valid for this spec
   Hdeq = design(d,'equiripple'); % FIR filter
   Hbutt = design(d,'butter'); %IIR design

MATLAB: How to bandpass eeg data

My filter design strategy is here: How to design a lowpass filter for ocean wave data in Matlab?

You will need two filters, one for each EEG band. Filter the EEG in parallel with them. Remember that for a band-pass filter, the stop-bands have to be outside (less than an greater than, respectively) of the pass-band frequencies. You will have to experiment to get the result you want. With such a low sampling frequency and narrow pass-bands for those EEG bands, a Chebyshev Type II filter would be my choice, with a pass-band ripple of 5 dB or less and a stop-band ripple of 50 dB or less.

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MATLAB: Fir and iir filtering

MATLAB: How to bandpass eeg data

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