electronics.circular_convolution
================================

.. py:module:: electronics.circular_convolution

.. autoapi-nested-parse::

   Circular convolution, also known as cyclic convolution,
   is a special case of periodic convolution, which is the convolution of two
   periodic functions that have the same period. Periodic convolution arises,
   for example, in the context of the discrete-time Fourier transform (DTFT).
   In particular, the DTFT of the product of two discrete sequences is the periodic
   convolution of the DTFTs of the individual sequences. And each DTFT is a periodic
   summation of a continuous Fourier transform function.

   Source: https://en.wikipedia.org/wiki/Circular_convolution



Classes
-------

.. autoapisummary::

   electronics.circular_convolution.CircularConvolution


Module Contents
---------------

.. py:class:: CircularConvolution

   This class stores the first and second signal and performs the circular convolution


   .. py:method:: circular_convolution() -> list[float]

      This function performs the circular convolution of the first and second signal
      using matrix method

      Usage:
      >>> convolution = CircularConvolution()
      >>> convolution.circular_convolution()
      [10.0, 10.0, 6.0, 14.0]

      >>> convolution.first_signal = [0.2, 0.4, 0.6, 0.8, 1.0, 1.2, 1.4, 1.6]
      >>> convolution.second_signal = [0.1, 0.3, 0.5, 0.7, 0.9, 1.1, 1.3, 1.5]
      >>> convolution.circular_convolution()
      [5.2, 6.0, 6.48, 6.64, 6.48, 6.0, 5.2, 4.08]

      >>> convolution.first_signal = [-1, 1, 2, -2]
      >>> convolution.second_signal = [0.5, 1, -1, 2, 0.75]
      >>> convolution.circular_convolution()
      [6.25, -3.0, 1.5, -2.0, -2.75]

      >>> convolution.first_signal = [1, -1, 2, 3, -1]
      >>> convolution.second_signal = [1, 2, 3]
      >>> convolution.circular_convolution()
      [8.0, -2.0, 3.0, 4.0, 11.0]




   .. py:attribute:: first_signal


   .. py:attribute:: second_signal
      :value: [1, 2, 3, 4]