MATLAB: Normalized Frequency in Analog Filter Design.

normalized frequency in analog filters.

Hi Everyone,

I am trying to design a butterworth analog filter in MATLAB. In this particular case I require a 3dB freq of 5MHz and an attenuation of -40dB at 10MHz (no more than 3dB ripple which isnt a concern here due to the maximally flat nature of the butterworth.)

In the MATLAB manuals, it is mentioned that I need to use butter (n,Wn,'s') to get the poles of the filter. I am not quite sure what value of Wn I am supposed to use. Has it to be normalized to some particular frequency or do I use 5×10(^6) here?(in this case I get a k of extremely large value (something^(46))).

Can someone suggest what I should be using for Wn?

Best Answer

Normalized frequency is for digital filters. If you want to design analog filters, they don't apply. Like you mentioned, you should use the syntax with 's' at the end. To get Wn, you can use buttord function (also has an 's' syntax for analog filter).

http://www.mathworks.com/help/signal/ref/buttord.html

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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 do i normalise frequency axis after computing fft

If you have a 50 Hz sampling frequency, the Nyquist frequency — in this instance the normalising frequency if you are designing a digital filter — is 25 Hz. So if you want a 15 Hz cutoff for a lowpass filter for instance, the normalised frequency, ‘Wn’ would be:

Fs = 50;                    % Sampling Frequency (Hz)
Fn = Fs/2;                  % Nyquist Frequency (Hz)
Fc = 15;                    % Cutoff Frequency (Hz)
Wn = Fc/Fn;                 % Normalised Cutoff Frequency (Dimensionless)

So Wn = 15/25 = 0.6

EDIT — For fft scaling, the best documentation is in the R2015a fft version. See specifically the code between the first two plot images.

Best Answer

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