Sentence examples for matrix multiplication between from inspiring English sources

Indeed, in this framework the convolution with g is nothing but the continuous matrix multiplication between v and a continuous Toeplitz matrix generated row by row by g.

Therefore, once the commutator reaches the top, the matrix multiplication between the input buffer and the filter coefficient matrix is complete.

We provide an inversion of group-based phylogenetic models that can implemented using matrix multiplication between rectangular matrices indexed by ordered-partitions of varying sizes.

When | I| = | J| = r (lines 4-9 in Procedure Compute-Inside-Sub-Matrix, Table 2), the algorithm performs two recursive calls with sub-matrices of size r × r 2, a matrix multiplication between an r × r 2 and an r 2 × r 2 matrices, and a matrix addition of two r × r 2 matrices.

When | I| = 2| J| = r (lines 10-15 in Procedure Compute-Inside-Sub-Matrix, Table 2), the algorithm performs two recursive calls with sub-matrices of size r 2 × r 2, a matrix multiplication between two r 2 × r 2 matrices, and a matrix addition of two r 2 × r 2 matrices.

(1) X 1 X 2 ⊗ Y = X 1 ⊗ Y X 2 ⊗ Y (2) X ⊗ [ Y 1 Y 2 ] = [ (X ⊗ Y 1 ) (X ⊗ Y 2 ) ] (3) (X 1 ⊗ Y 1 ) ⊕ (X 2 ⊗ Y 2 ) = [ X 1 X 2 ] ⊗ Y 1 Y 2 Under the assumption that the operations ⊗ and ⊕ between two domain elements consume Θ(1) computation time, a straightforward implementation of a matrix multiplication between two n × n matrices can be computed in Θ(n) time.

In order to maintain a required precondition, the procedure applies min-plus matrix multiplication subroutines between recursive calls.

The accelerated computation of values of the form μ i, j is obtained by the application of fast matrix multiplication subroutines between sibling recursive calls of the algorithm.

Taking into account the inherent matrix multiplication required to compute the distance between STBC codewords V j and W j (cf. (3)), the computation complexity of the soft demapper becomes of the magnitude order O((q - 1) × qm 1-1× m3 × n r × Q × T).

Under the 1-to-1 correspondence between matrices and linear maps, matrix multiplication corresponds to composition of maps: if a k-by-m matrix B represents another linear map g Rm → Rk, then the composition g ∘ f is represented by BA since :(g ∘ f)('x') = g(f('x')) = g(Ax) = B(Ax) = (BA)'x'x

Expansion corresponds to matrix multiplication, which is responsible for creating new edges, while inflation increases the contrasts between existing differences of probability.