Convolution with np.convolve() in NumPy - Mini Project: Build & Apply

Convolution with np.convolve()

📖 Scenario: Imagine you are analyzing a simple signal in a sensor. You want to smooth the signal by combining it with a small filter that averages nearby points. This process is called convolution and helps reduce noise in the data.

🎯 Goal: You will create two arrays: one for the signal and one for the filter. Then you will use np.convolve() to combine them and see the smoothed result.

📋 What You'll Learn

Create a numpy array called signal with the values [1, 2, 3, 4, 5]

Create a numpy array called filter with the values [0.2, 0.5, 0.3]

Use np.convolve() with signal and filter to compute the convolution

Print the convolution result

💡 Why This Matters

🌍 Real World

Convolution is used in signal processing, image filtering, and data smoothing to reduce noise and extract features.

💼 Career

Understanding convolution helps in roles like data analyst, machine learning engineer, and signal processing specialist.

1

Create the signal array

Create a numpy array called signal with these exact values: [1, 2, 3, 4, 5]

NumPy

import numpy as np
# Create the signal array with values [1, 2, 3, 4, 5]
# Your code here

Need a hint?

Use np.array() to create the array with the exact values.

2

Create the filter array

Create a numpy array called filter with these exact values: [0.2, 0.5, 0.3]

NumPy

import numpy as np
signal = np.array([1, 2, 3, 4, 5])
# Create the filter array with values [0.2, 0.5, 0.3]
# Your code here

Need a hint?

Use np.array() to create the filter array with the exact values.

3

Compute the convolution

Use np.convolve() with signal and filter to compute the convolution and store the result in a variable called convolved

NumPy

import numpy as np
signal = np.array([1, 2, 3, 4, 5])
filter = np.array([0.2, 0.5, 0.3])
# Compute the convolution of signal and filter
# Your code here

Need a hint?

Use np.convolve(signal, filter) to get the combined array.

4

Print the convolution result

Print the variable convolved to display the convolution result

NumPy

import numpy as np
signal = np.array([1, 2, 3, 4, 5])
filter = np.array([0.2, 0.5, 0.3])
convolved = np.convolve(signal, filter)
# Print the convolution result
# Your code here

Need a hint?

Use print(convolved) to show the result.