This example illustrates the design of a 5th-order Butterworth lowpass filter, implementing it using second-order sections. Since all three sections contribute to the same passband and stopband, it is numerically advisable to choose a series second-order-section implementation, so that their passbands and stopbands will multiply together instead of add.
fc = 1000; % Cut-off frequency (Hz) fs = 8192; % Sampling rate (Hz) order = 5; % Filter order [B,A] = butter(order,2*fc/fs); % [0:pi] maps to [0:1] here [sos,g] = tf2sos(B,A) % sos = % 1.00000 2.00080 1.00080 1.00000 -0.92223 0.28087 % 1.00000 1.99791 0.99791 1.00000 -1.18573 0.64684 % 1.00000 1.00129 -0.00000 1.00000 -0.42504 0.00000 % % g = 0.0029714 % % Compute and display the amplitude response Bs = sos(:,1:3); % Section numerator polynomials As = sos(:,4:6); % Section denominator polynomials [nsec,temp] = size(sos); nsamps = 256; % Number of impulse-response samples % Note use of input scale-factor g here: x = g*[1,zeros(1,nsamps-1)]; % SCALED impulse signal for i=1:nsec x = filter(Bs(i,:),As(i,:),x); % Series sections end % %plot(x); % Plot impulse response to make sure % it has decayed to zero (numerically) % % Plot amplitude response % (in Octave - Matlab slightly different): figure(2); X=fft(x); % sampled frequency response f = [0:nsamps-1]*fs/nsamps; grid('on'); axis([0 fs/2 -100 5]); legend('off'); plot(f(1:nsamps/2),20*log10(X(1:nsamps/2)));The final plot appears in Fig.9.7. A Matlab function for frequency response plots is given in §J.4. (Of course, one can also use freqz in either Matlab or Octave.)
Note that the Matlab Signal Processing Toolbox has a function called sosfilt so that ``y=sosfilt(sos,x)'' will implement an array of series second-order sections without having to unpack them first as in the example above.