# 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  12``````

This 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}:
32``````

In 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}:
2``````

Here, 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`.