Ac_mul_Bc
Ac_mul_Bc(A, B)
For matrices or vectors $A$ and $B$, calculates $Aá´´ Bá´´$
Examples
julia> A = [1 2; 3 4];
julia> B = [2 0; 1 2];
julia> Ac_mul_Bc(A, B)
2×2 Array{Int64,2}:
4 4
10 12This example demonstrates the usage of the Ac_mul_Bc function to calculate the conjugate transpose of matrix A multiplied by the conjugate transpose of matrix B.
julia> A = [1 2 3];
julia> B = [4; 5; 6];
julia> Ac_mul_Bc(A, B)
1-element Array{Int64,1}:
32In this example, A is a row vector and B is a column vector. The Ac_mul_Bc function calculates the conjugate transpose of A multiplied by the conjugate transpose of B, resulting in a scalar value.
julia> A = [1];
julia> B = [2];
julia> Ac_mul_Bc(A, B)
1-element Array{Int64,1}:
2Here, both A and B are single-element vectors. The function calculates the conjugate transpose of A multiplied by the conjugate transpose of B, resulting in a single-element vector.
julia> A = [1 2; 3 4];
julia> B = [2 0 1; 1 2 3];
julia> Ac_mul_Bc(A, B)
ERROR: DimensionMismatch("A has dimensions (2,2) but B has dimensions (2,3)")If the dimensions of A and B are not compatible for matrix multiplication, an error will be raised. In this example, the number of columns in A does not match the number of rows in B, leading to a DimensionMismatch error. Make sure the dimensions of the matrices or vectors are compatible when using Ac_mul_Bc.
See Also
Ac_ldiv_B, Ac_ldiv_Bc, Ac_mul_B, Ac_mul_Bc, Ac_rdiv_B, Ac_rdiv_Bc, At_ldiv_B, At_ldiv_Bt, At_mul_B, At_mul_Bt, At_rdiv_B, At_rdiv_Bt, A_ldiv_Bc, A_ldiv_Bt, A_mul_B!, A_mul_Bc, A_mul_Bt, A_rdiv_Bc, A_rdiv_Bt, Bidiagonal, cond, conv2, det, diag, diagind, diagm, diff, eig, eigvals, eigvecs, expm, eye, full, inv, isdiag, ishermitian, isposdef, isposdef!, issym, istril, istriu, logabsdet, logdet, lyap, norm, qrfact, rank, repmat, rot180, rotl90, rotr90, sortrows, sqrtm, SymTridiagonal, trace, Tridiagonal, tril, tril!, triu, triu!, writedlm,User Contributed Notes
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