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# Tag Info

## Hot answers tagged filter-design

3

This happens frequently if your poles are reasonably close to the unit circle. Consider the following example %% TF2ZP is problematic fs = 44100; % 6th order lowpass, fc = 50Hz, sampled at 44.1kHz [z,p,k] = cheby2(6,80,50*2/fs); % to transfer function [b,a] = zp2tf(z,p,k); % back to zpk [z1,p1,k1] = tf2zp(b,a); display([p p1]); Displaying the poles side ...

2

It is better to "parse" these networks from the output back towards the input, calling their input some general $x$ and performing substitutions and/or compositions. So, let's call these networks $U$pper and $L$ower. From the upper diagram: $$UH_2[n] = x[n] + x[n-1] \cdot -a_1$$ and $$UH_1[n] = x[n] \cdot b_0+x[n-1] \cdot b_1$$ Now, the output of $U$...

2

You have a very narrow stop band which means that all the poles are crammed in a very small area of the complex plane, close to the unit circle. This can result in severe numerical problems, even for relatively small filter orders, even with floating point arithmetic. Another important point that you might not realize is that if you design a band pass or a ...

1

I suppose that you obtain a transfer function of the desired discrete-time system in the form $$H(z)=\frac{b_0+b_1z^{-1}+\ldots +b_Nz^{-N}}{1+a_1z^{-1}+\ldots +a_Nz^{-N}}\tag{1}$$ From that transfer function you compute the coefficients of the second-order sections. Before doing that, you can make sure that the DC gain of $(1)$ equals $1$ (which of course ...

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