| + | Matrix addition. A+B adds A and B. A and B must have
the same dimensions, unless one is scalar. |
| - | Matrix subtraction. A-B subtracts B from A. A and B must have
the same dimensions, unless one is scalar. |
| * | Matrix multiplication. A*B is the linear algebraic product of A and B. The number of columns of A must equal the number of rows of B, unless one is a scalar. |
| .* | Array multiplication. A.*B is the entry-by-entry product of A and B. A and B must have the same dimensions, unless one is scalar. |
| \ | Matrix left division. A\B solves the symbolic linear equations A*X=B for X. Note that A\B is roughly equivalent
to inv(A)*B. Warning messages are produced if X does not exist or is not unique. Rectangular matrices A are allowed, but the equations must be consistent; a
least squares solution is not computed. |
| .\ | Array left division. A.\B is the matrix with entries B(i,j)/A(i,j). A and B must have the same dimensions,
unless one is scalar. |
| / | Matrix right division. B/A solves the symbolic linear equation X*A=B for X. Note that B/A is the
same as (A.'\B.').'. Warning messages are produced
if X does not exist or is not unique. Rectangular
matrices A are allowed, but the equations must
be consistent; a least squares solution is not computed. |
| ./ | Array right division. A./B is the matrix with entries A(i,j)/B(i,j). A and B must have the same dimensions,
unless one is scalar. |
| ^ | Matrix power. A^B raises the square matrix A to the integer power B. If A is a scalar and B is a square matrix, A^B raises A to the matrix power B, using eigenvalues and eigenvectors. A^B, where A and B are both matrices,
is an error. |
| .^ | Array power. A.^B is the matrix with entries A(i,j)^B(i,j). A and B must have the same dimensions, unless one is scalar. |
| ' | Matrix Hermition
transpose. If A is complex, A' is the complex conjugate transpose. |
| .' | Array transpose. A.' is the real transpose of A. A.' does not conjugate complex entries. |
