Multidimensional discrete convolution: Difference between revisions

Revision as of 11:22, 20 May 2017

Revision as of 09:31, 18 July 2017

Line 147:

<math>y(n)=h(n)\otimes x(n)\longleftrightarrow Y(k)=H(k)X(k)</math>

When dealing with signals of multiple dimensions:<math display="block">y(n_1,n_2,...,n_M)=h(n_1,n_2,...,n_M)\otimes\overset{M}{\cdots}\otimes x(n_1,n_2,...,n_M) \longleftrightarrow Y(k_1,k_2,...,k_M)=H(k_1,k_2,...,k_M)X(k_1,k_2,...,k_M)</math>The circular convolutions here will be of size <math>N_1, N_2,...,N_M</math>.

===Circular Convolution Approach===