# Design IIR Highpass Filters

This post is the fourth in a series of tutorials on IIR Butterworth filter design. So far we covered lowpass [1], bandpass [2], and band-reject [3] filters; now we’ll design highpass filters. The general approach, as before, has six steps:

- Find the poles of a lowpass analog prototype filter with Ω
_{c}= 1 rad/s. - Given the -3 dB frequency of the digital highpass filter, find the corresponding frequency of the analog highpass filter (pre-warping).
- Transform the analog lowpass poles to analog highpass poles.
- Transform the poles from the s-plane to the z-plane, using the bilinear transform.
- Add N zeros at z= 1, where N is the filter order.
- Convert poles and zeros to polynomials with coefficients a
_{n}and b_{n}.

This article is available in PDF format for easy printing.

The detailed design procedure follows. Recall from the previous posts that F is continuous (analog) frequency in Hz and Ω is continuous radian frequency. A Matlab function hp_synth that performs the filter synthesis is provided in the Appendix. Note that hp_synth(N,fc,fs) gives the same results as the Matlab function butter(N,2*fc/fs,’high’).

1. Poles of the analog lowpass prototype filter. For a Butterworth filter of order N with Ω_{c} = 1 rad/s, the poles are given by [4, 5]:

$$p_{ak}= -sin(\theta)+jcos(\theta)$$

where $$\theta=\frac{(2k-1)\pi}{2N},\quad k=1:N$$

Here we use a prime superscript on p to distinguish the lowpass prototype poles from the yet to be calculated highpass poles.

2. Given the -3 dB discrete frequency f_{c} of the digital highpass filter, find the corresponding frequency of the analog highpass filter. As before, we’ll adjust (pre-warp) the analog frequency to take the nonlinearity of the bilinear transform into account:

$$F_c=\frac{f_s}{\pi}tan\left(\frac{\pi f_c}{f_s}\right)$$

3. Transform the normalized analog lowpass poles to analog highpass poles. For each lowpass pole p_{a}’, we get the highpass pole [6, 7]:

$$p_a=2\pi F_c/p'_a$$

4. Transform the
poles from the s-plane to the z-plane, using the bilinear transform [1]:

$$p_k=\frac{1+p_{ak}/(2f_s)}{1-p_{ak}/(2f_s)},\quad
k=1:N$$

5. Add N zeros at z= 1. The N^{th}-order highpass filter has
N zeros at ω= 0, or z= exp(j0) = 1. We
can now write H(z) as:

$$H(z)=K\frac{(z-1)^N}{(z-p_1)(z-p_2)...(z-p_{N})}\qquad(1)$$

In hp_synth, we represent the N zeros at +1 as a vector:

q= ones(1,N)

6. Convert poles and zeros to polynomials with coefficients a_{n} and b_{n}. If we expand the numerator and denominator of equation 1 and divide numerator and denominator by z^{N}, we get polynomials in z^{-n}:

$$H(z)=K\frac{b_0+b_1z^{-1}+...+b_Nz^{-N}}{1+a_1z^{-1}+...+a_Nz^{-N}}\qquad(2)$$

The Matlab code to perform the expansion is:

a= poly(p) a= real(a) b= poly(q)

Given that H(z) is highpass, we want H(z) to have a gain of 1 at f = f_{s}/2, that is, at ω= π. At ω= π, z = exp(jπ) = -1. Referring to equation 2, we then have gain at ω= π of:

$$H(z=-1)=1=K\frac{\sum_{m=0}^N(-1)^m*b_m}{\sum_{m=0}^N(-1)^m*a_m}$$

So we have:

$$K= \frac{\sum_{m=0}^N(-1)^m*a_m}{\sum_{m=0}^N(-1)^m*b_m}$$

## Example

Here is an example function call for a 5^{th} order highpass filter:

N= 5; % filter order fc= 40; % Hz -3 dB frequency fs= 100; % Hz sample frequency [b,a]= hp_synth(N,fc,fs) b = 0.0013 -0.0064 0.0128 -0.0128 0.0064 -0.0013 a = 1.0000 2.9754 3.8060 2.5453 0.8811 0.1254

To find the frequency response:

[h,f]= freqz(b,a,512,fs); H= 20*log10(abs(h));

The resulting response is shown in Figure 1, along
with the responses for N= 2, 3, and 7.
The pole-zero plot in the z-plane is shown in Figure 2.

Figure 1. Magnitude Response of Butterworth highpass filters for various filter orders.

f_{c} = 40 Hz and f_{s} = 100 Hz.

Figure 2. Pole-zero plot of 5^{th} order Butterworth highpass filter. f_{c} = 40 Hz and f_{s} = 100 Hz.

Zero at z= 1 is 5^{th} order.

## References

1. Robertson, Neil , “Design IIR Butterworth Filters Using 12 Lines of Code”, Dec 2017 https://www.dsprelated.com/showarticle/1119.php

2. Robertson, Neil , “Design IIR Bandpass Filters”, Jan 2017 https://www.dsprelated.com/showarticle/1128.php

3. Robertson, Neil , “Design IIR Band-Reject Filters”, Jan 2017 https://www.dsprelated.com/showarticle/1131.php

4. Williams, Arthur B. and Taylor, Fred J., __Electronic Filter Design Handbook__, 3^{rd} Ed., McGraw-Hill, 1995, section 2.3

5. Analog Devices Mini Tutorial MT-224, 2012 http://www.analog.com/media/en/training-seminars/tutorials/MT-224.pdf

6. Blinchikoff, Herman J., and Zverev,Anatol I., Filtering in the Time and Frequency Domains, Wiley, 1976, section 4.3.

7. Nagendra Krishnapura , “E4215: Analog Filter Synthesis and Design Frequency Transformation”, 4 Mar. 2003 http://www.ee.iitm.ac.in/~nagendra/E4215/2003/handouts/freq_transformation.pdf

Neil Robertson February, 2018

## Appendix Matlab Function hp_synth.m

This program is provided as-is without any guarantees or warranty. The author is not responsible for any damage or losses of any kind caused by the use or misuse of the program.

% hp_synth.m 1/30/18 Neil Robertson % Find the coefficients of an IIR Butterworth highpass filter using bilinear transform. % % N= filter order % fc= -3 dB frequency in Hz % fs= sample frequency in Hz % b = numerator coefficients of digital filter % a = denominator coefficients of digital filter % function [b,a]= hp_synth(N,fc,fs); if fc>=fs/2; error('fc must be less than fs/2') end % I. Find poles of normalized analog lowpass filter k= 1:N; theta= (2*k -1)*pi/(2*N); p_lp= -sin(theta) + j*cos(theta); % poles of lpf with cutoff = 1 rad/s % II. transform poles for hpf Fc= fs/pi * tan(pi*fc/fs); % continuous pre-warped frequency pa= 2*pi*Fc./p_lp; % analog hp poles % III. Find coeffs of digital filter % poles and zeros in the z plane p= (1 + pa/(2*fs))./(1 - pa/(2*fs)); % poles by bilinear transform q= ones(1,N); % zeros at z = 1 (f= 0) % convert poles and zeros to polynomial coeffs a= poly(p); % convert poles to polynomial coeffs a a= real(a); b= poly(q); % convert zeros to polynomial coeffs b % amplitude scale factor for gain = 1 at f = fs/2 (z = -1) m= 0:N; K= sum((-1).^m .*a)/sum((-1).^m .*b); % amplitude scale factor b= K*b;

**Previous post by Neil Robertson:**

Design IIR Band-Reject Filters

**Next post by Neil Robertson:**

Design IIR Filters Using Cascaded Biquads

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