I know that, in the 1D case, the convolution between two vectors, a and b, can be computed as conv(a, b), but also as the product between the T_a and b, where T_a is the corresponding Toeplitz matrix for a.

Is it possible to extend this idea to 2D?

Given a = [5 1 3; 1 1 2; 2 1 3] and b=[4 3; 1 2], is it possible to convert a in a Toeplitz matrix and compute the matrix-matrix product between T_a and b as in the 1-D case?

neural-network deep-learning conv-neural-network matrix-multiplication convolution
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