MATLAB: How to calculate prewardped frequency in analog domain

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How to approach the problem of calculating prewarped frequency in analog domain if I have to use bilinear z-transform? Sampling frequency of 20kHz and band edges of IIR BPF digital filter as 4 and 7khz.

How to do this in matlab?

Best Answer

The prewarping frequency in the analog domain is whatever you want it to be. I usually choose the corner frequency of a highpass or lowpass filter, or the centre frequency of the bandpass or stopband in those filters. For a filter with multiple passbands and stopbands (rare), I choose the frequency that is half the Nyquist frequency. That also works if you simply can’t decide.

Essentially, it needs to be whatever will produce the best filter in the discrete domain after the transformation. As with everything else in signal processing, this usually requires some experimentation to get the result you want. Always use the freqz function to see what your filter is doing before you actually filter with it. And always use the filtfilt function to do the actual filtering.

Related Solutions

MATLAB: How to design FIR lowpass filter with cutoff frequency, fc1 = 20 Hz and FIR bandpass filter with cutoff frequency fc2 = 10 Hz and fc3 = 35 Hz.

Déjà vu

how to design IIR highpass filter with cutoff frequency of 20Hz and FIR bandpass filter with cutoff frequency of 10Hz and 15Hz?

Make the appropriate changes to get the cascaded filter you want.

MATLAB: How to Butterworth Filter with Bandpass [10 500] with sampling rate 1000

You have to divide your passband and stopband frequencies by the Nyquist frequency to normalise them:

Fs = 1000;                                          % Sampling Frequency
Fn = Fs/2;                                          % Nyquist Frequency
Wp = [10  495]/Fn;                                  % Norrmalised Passband Frequencies
Ws = [5   499]/Fn;                                  % Normalised Stopband Frequencies
Rp =  1;                                            % Passband Ripple (dB)
Rs = 25;                                            % Stopband Ripple (dB)
[n,Wn] = buttord(Wp, Ws, Rp, Rs);                   % Optimal Filter Order
[b,a] = butter(n, Wn);                              % Calculate Filter Coefficients
[sos,g] = tf2sos(b,a);                              % Convert To Second-Order Sections For Stability
figure(1)
freqz(sos, 4096, Fs)                                % Filter Bode Plot

You cannot have any frequency exactly at zero or exactly at the Nyquist frequency, so I designed your passband to be close enough to them to be stable. In your filter, you can also use a high-pass design with a lower cutoff of 10 Hz, since your upper passband is at the Nyquist frequency. The passband and stopband ripple values are necessary to specify in the design but irrelevant to a Butterworth filter. These are acceptable values for most filter designs (for example Chebyshev) that require them.

You would use the ‘sos’ and ‘g’ variables in your actual filter:

filtered_signal = filtfilt(sos, g, signal);

(This design works well in R2016a and should also work in earlier releases.)

Best Answer

Related Solutions

MATLAB: How to design FIR lowpass filter with cutoff frequency, fc1 = 20 Hz and FIR bandpass filter with cutoff frequency fc2 = 10 Hz and fc3 = 35 Hz.

MATLAB: How to Butterworth Filter with Bandpass [10 500] with sampling rate 1000

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