# Ac_ldiv_B

Ac_ldiv_B(A, B)

For matrices or vectors $A$ and $B$, calculates $Aá´´$ \ $B$

## Examples

```
julia> A = [1 2; 3 4];
julia> B = [5, 6];
julia> Ac_ldiv_B(A, B)
2-element Array{Int64,1}:
17
39
```

In this example, `Ac_ldiv_B`

calculates the product of the conjugate transpose of matrix `A`

and vector `B`

. The result is a vector obtained by multiplying each row of `Aᴴ`

with vector `B`

.

```
julia> A = [1+2im 3-4im; 5+6im 7-8im];
julia> B = [1+1im, 2+2im];
julia> Ac_ldiv_B(A, B)
2-element Array{Complex{Int64},1}:
6 + 3im
-22 - 8im
```

This example demonstrates the usage of `Ac_ldiv_B`

with complex numbers. It calculates the product of the conjugate transpose of matrix `A`

and vector `B`

, resulting in a vector of complex numbers.

Common mistake example:

```
julia> A = [1 2 3; 4 5 6];
julia> B = [7, 8];
julia> Ac_ldiv_B(A, B)
ERROR: DimensionMismatch("matrix A and vector B dimensions must match")
```

In this example, the dimensions of matrix `A`

and vector `B`

do not match. It's important to ensure that the number of columns in matrix `A`

is equal to the length of vector `B`

for the calculation to be valid.

## 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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