FIR filter design (firwin) in SciPy - Mini Project: Build & Apply

FIR Filter Design Using firwin

📖 Scenario: You are working with sound signals and want to remove high-frequency noise. A common way to do this is by designing a low-pass filter that keeps only the low frequencies you want.We will use a simple method to create this filter called firwin from the scipy library.

🎯 Goal: Build a low-pass FIR filter using firwin to keep frequencies below 0.3 times the Nyquist frequency.You will create the filter coefficients, set the filter length, and then print the coefficients.

📋 What You'll Learn

Create a variable called numtaps with the value 21 for the filter length.

Create a variable called cutoff with the value 0.3 for the cutoff frequency.

Use firwin from scipy.signal to create the filter coefficients in a variable called fir_coeff.

Print the fir_coeff array to see the filter values.

💡 Why This Matters

🌍 Real World

FIR filters are used in audio processing, communications, and many engineering fields to remove unwanted frequencies from signals.

💼 Career

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

1

Set the filter length

Create a variable called numtaps and set it to 21. This number controls how many coefficients the filter will have.

SciPy

# Create a variable called numtaps and set it to 21
# Your code here

Need a hint?

The filter length is the number of taps or coefficients. Use numtaps = 21.

2

Set the cutoff frequency

Create a variable called cutoff and set it to 0.3. This is the cutoff frequency as a fraction of the Nyquist frequency.

SciPy

numtaps = 21
# Create a variable called cutoff and set it to 0.3
# Your code here

Need a hint?

The cutoff frequency is between 0 and 1, where 1 means the Nyquist frequency. Use cutoff = 0.3.

3

Create the FIR filter coefficients

Import firwin from scipy.signal and use it to create the filter coefficients. Store the result in a variable called fir_coeff by calling firwin(numtaps, cutoff).

SciPy

numtaps = 21
cutoff = 0.3
# Import firwin from scipy.signal and create fir_coeff using firwin(numtaps, cutoff)
# Your code here

Need a hint?

Use from scipy.signal import firwin to import, then fir_coeff = firwin(numtaps, cutoff).

4

Print the filter coefficients

Print the variable fir_coeff to see the filter coefficients.

SciPy

from scipy.signal import firwin

numtaps = 21
cutoff = 0.3

fir_coeff = firwin(numtaps, cutoff)
# Print the fir_coeff array
# Your code here

Need a hint?

Use print(fir_coeff) to display the coefficients.