# issymmetric

Determine if matrix is symmetric or skew-symmetric

## Description

example

tf = issymmetric(A) returns logical 1 (true) if square matrix A is symmetric; otherwise, it returns logical 0 (false).

example

tf = issymmetric(A,skewOption) specifies the type of the test. Specify skewOption as 'skew' to determine if A is skew-symmetric.

## Examples

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Create a 3-by-3 matrix.

A = [1 0 1i; 0 1 0;-1i 0 1]
A = 3×3 complex

1.0000 + 0.0000i   0.0000 + 0.0000i   0.0000 + 1.0000i
0.0000 + 0.0000i   1.0000 + 0.0000i   0.0000 + 0.0000i
0.0000 - 1.0000i   0.0000 + 0.0000i   1.0000 + 0.0000i

The matrix is Hermitian and has a real-valued diagonal.

Test whether the matrix is symmetric.

tf = issymmetric(A)
tf = logical
0

The result is logical 0 (false) because A is not symmetric. In this case, A is equal to its complex conjugate transpose, A', but not its nonconjugate transpose, A.'.

Change the element in A(3,1) to be 1i.

A(3,1) = 1i;

Determine whether the modified matrix is symmetric.

tf = issymmetric(A)
tf = logical
1

The matrix, A, is now symmetric because it is equal to its nonconjugate transpose, A.'.

Create a 4-by-4 matrix.

A = [0 1 -2 5; -1 0 3 -4; 2 -3 0 6; -5 4 -6 0]
A = 4×4

0     1    -2     5
-1     0     3    -4
2    -3     0     6
-5     4    -6     0

The matrix is real and has a diagonal of zeros.

Specify skewOption as 'skew' to determine whether the matrix is skew-symmetric.

tf = issymmetric(A,'skew')
tf = logical
1

The matrix, A, is skew-symmetric since it is equal to the negation of its nonconjugate transpose, -A.'.

## Input Arguments

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Input matrix, specified as a numeric matrix. If A is not square, then issymmetric returns logical 0 (false).

Data Types: single | double | logical
Complex Number Support: Yes

Test type, specified as 'nonskew' or 'skew'. Specify 'skew' to test whether A is skew-symmetric.

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### Symmetric Matrix

• A square matrix, A, is symmetric if it is equal to its nonconjugate transpose, A = A.'.

In terms of the matrix elements, this means that

${a}_{i,\text{\hspace{0.17em}}j}={a}_{j,\text{\hspace{0.17em}}i}\text{\hspace{0.17em}}\text{\hspace{0.17em}}.$

• Since real matrices are unaffected by complex conjugation, a real matrix that is symmetric is also Hermitian. For example, the matrix

$A=\left[\begin{array}{cc}\begin{array}{cc}\begin{array}{c}1\\ 0\end{array}& \begin{array}{c}0\\ 2\end{array}\end{array}& \begin{array}{c}1\\ 0\end{array}\\ \begin{array}{cc}1& 0\end{array}& 1\end{array}\right]$

is both symmetric and Hermitian.

### Skew-Symmetric Matrix

• A square matrix, A, is skew-symmetric if it is equal to the negation of its nonconjugate transpose, A = -A.'.

In terms of the matrix elements, this means that

${a}_{i,\text{\hspace{0.17em}}j}=-{a}_{j,\text{\hspace{0.17em}}i}\text{\hspace{0.17em}}\text{\hspace{0.17em}}.$

• Since real matrices are unaffected by complex conjugation, a real matrix that is skew-symmetric is also skew-Hermitian. For example, the matrix

$A=\left[\begin{array}{cc}0& -1\\ 1& \text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}0\end{array}\right]$

is both skew-symmetric and skew-Hermitian.

## Version History

Introduced in R2014a