IIR filter design (butter, cheby1) in SciPy - Mini Project: Build & Apply

IIR Filter Design with Butterworth and Chebyshev Type I Filters

📖 Scenario: You are working on a project to clean noisy sensor data. To do this, you need to design digital filters that remove unwanted frequencies.Two common filters are Butterworth and Chebyshev Type I filters. They help keep the important signals while reducing noise.

🎯 Goal: You will create two digital filters using scipy.signal: a Butterworth filter and a Chebyshev Type I filter. Then, you will print their filter coefficients.

📋 What You'll Learn

Use scipy.signal.butter to create a Butterworth filter

Use scipy.signal.cheby1 to create a Chebyshev Type I filter

Set filter order to 4

Set cutoff frequency to 0.3 (normalized frequency)

Print the filter coefficients for both filters

💡 Why This Matters

🌍 Real World

Digital filters like Butterworth and Chebyshev are used in audio processing, sensor data cleaning, and communication systems to remove noise and unwanted signals.

💼 Career

Understanding how to design and use IIR filters is important for roles in signal processing, data analysis, and embedded systems engineering.

1

Create filter order and cutoff frequency variables

Create a variable called order and set it to 4. Create another variable called cutoff and set it to 0.3.

SciPy

# Create variables order and cutoff
# Your code here

Need a hint?

Use simple assignment like order = 4 and cutoff = 0.3.

2

Import butter and cheby1 functions from scipy.signal

Import butter and cheby1 from scipy.signal.

SciPy

order = 4
cutoff = 0.3
# Import butter and cheby1 from scipy.signal
# Your code here

Need a hint?

Use from scipy.signal import butter, cheby1 to import both functions.

3

Create Butterworth and Chebyshev Type I filters

Use butter with order and cutoff to create a lowpass Butterworth filter. Save the output as b_butter and a_butter. Use cheby1 with order, ripple of 1, and cutoff to create a lowpass Chebyshev Type I filter. Save the output as b_cheby and a_cheby.

SciPy

order = 4
cutoff = 0.3
from scipy.signal import butter, cheby1
# Create Butterworth filter coefficients
# Create Chebyshev Type I filter coefficients
# Your code here

Need a hint?

Use butter(order, cutoff, btype='low') and cheby1(order, 1, cutoff, btype='low').

4

Print the filter coefficients

Print the variables b_butter, a_butter, b_cheby, and a_cheby each on a separate line.

SciPy

order = 4
cutoff = 0.3
from scipy.signal import butter, cheby1
b_butter, a_butter = butter(order, cutoff, btype='low')
b_cheby, a_cheby = cheby1(order, 1, cutoff, btype='low')
# Print the filter coefficients
# Your code here

Need a hint?

Use four print statements, one for each coefficient array.