# Return the discrete linear convolution of two one-dimensional sequences and return the middle values in Python

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To return the discrete linear convolution of two one-dimensional sequences, use the numpy.convolve() method in Python Numpy. The convolution operator is often seen in signal processing, where it models the effect of a linear time-invariant system on a signal. In probability theory, the sum of two independent random variables is distributed according to the convolution of their individual distributions. If v is longer than a, the arrays are swapped before computation.

The method returns the Discrete, linear convolution of a and v. The 1st parameter, a is the first onedimensional input array. The 2nd parameter, v is the second one-dimensional input array. The 3rd parameter, mode is optional, with values full’, ‘valid’, ‘same’. The mode ‘same’ returns output of length max(M, N). Boundary effects are still visible.

## Steps

At first, import the required libraries −

import numpy as np

Creating two numpy One-Dimensional array using the array() method −

arr1 = np.array([1, 2, 3])
arr2 = np.array([0, 1, 0.5])

Display the arrays −

print("Array1...",arr1)
print("Array2...",arr2)

Check the Dimensions of both the arrays −

print("Dimensions of Array1...",arr1.ndim)
print("Dimensions of Array2...",arr2.ndim)

Check the Shape of both the arrays −

print("Shape of Array1...",arr1.shape)
print("Shape of Array2...",arr2.shape)

To return the discrete linear convolution of two one-dimensional sequences, use the numpy.convolve() method −

print("Result....",np.convolve(arr1, arr2, mode = 'same' ))


## Example

import numpy as np

# Creating two numpy One-Dimensional array using the array() method
arr1 = np.array([1, 2, 3])
arr2 = np.array([0, 1, 0.5])

# Display the arrays
print("Array1...",arr1)
print("Array2...",arr2)

# Check the Dimensions of both the arrays
print("Dimensions of Array1...",arr1.ndim)
print("Dimensions of Array2...",arr2.ndim)

# Check the Shape of both the arrays
print("Shape of Array1...",arr1.shape)
print("Shape of Array2...",arr2.shape)

# To return the discrete linear convolution of two one-dimensional sequences, use the numpy.convolve() method in Python Numpy
print("Result....",np.convolve(arr1, arr2, mode = 'same' ))

## Output

Array1...
[1 2 3]

Array2...
[0. 1. 0.5]

Dimensions of Array1...
1

Dimensions of Array2...
1

Shape of Array1...
(3,)

Shape of Array2...
(3,)

Result....
[1. 2.5 4. ]
Updated on 01-Mar-2022 07:17:19