Symmetry pattern of a persymmetric (5 × 5) matrix
In mathematics, a persymmetric matrix is a square matrix that is symmetric with respect to its counter-diagonal .
definition
A square matrix over a body is called persymmetric if for its entries
![K](https://wikimedia.org/api/rest_v1/media/math/render/svg/2b76fce82a62ed5461908f0dc8f037de4e3686b0)
![a_ {i, j} = a_ {n-j + 1, n-i + 1}](https://wikimedia.org/api/rest_v1/media/math/render/svg/9fbd2c9a3219345bc8eb93b2163e02f549e15dc4)
for applies. The entries of a persymmetrical matrix do not change if they are mirrored on the opposite diagonal.
![i, j = 1, \ ldots, n](https://wikimedia.org/api/rest_v1/media/math/render/svg/897bfad1971b523f8c3eff622ac4ed7e2e0ae5b0)
Examples
For example, a real persymmetric matrix of size is
![3 times 3](https://wikimedia.org/api/rest_v1/media/math/render/svg/ddc0d4d6106875f8006be1d898512ca5843bad8e)
![A = \ begin {pmatrix} 1 & 2 & 3 \\ 2 & 3 & 2 \\ 3 & 2 & 1 \ end {pmatrix}](https://wikimedia.org/api/rest_v1/media/math/render/svg/3f292129282f1fca955d08cdb616d9d8554fbaaa)
Generally, persymmetric matrices of size have the form
![3 times 3](https://wikimedia.org/api/rest_v1/media/math/render/svg/ddc0d4d6106875f8006be1d898512ca5843bad8e)
![A = \ begin {pmatrix} a & b & c \\ d & e & b \\ f & d & a \ end {pmatrix}](https://wikimedia.org/api/rest_v1/media/math/render/svg/26908a2e95da56b2faa9eb800a017dcae53c8ca1)
with .
![a, b, c, d, e, f \ in K](https://wikimedia.org/api/rest_v1/media/math/render/svg/a7411760f0f3c6a72c96b021f042ce7f55e1ce50)
properties
Symmetries
With the permutation matrix defined by
![J \ in K ^ {n \ times n}](https://wikimedia.org/api/rest_v1/media/math/render/svg/461ada07509e5839b9924cc3ff6fb47b68242d8c)
![{\ displaystyle J = (\ delta _ {i, n-j + 1}) _ {ij} = {\ begin {pmatrix} 0 && 1 \\ & \ cdot ^ {\, \ cdot ^ {\, \ cdot}} & \\ 1 && 0 \ end {pmatrix}}}](https://wikimedia.org/api/rest_v1/media/math/render/svg/369b732a9021f35423cfd9744c0dc1029a9c96b0)
Persymmetric matrices can also be made compact by the condition
![YES = A ^ TJ](https://wikimedia.org/api/rest_v1/media/math/render/svg/acd1d1415d6b2a3cf17719ed504e352116e6f51d)
characterize. A bisymmetrical matrix is a persymmetrical matrix that is also symmetrical or centrally symmetrical . A Toeplitz matrix is a persymmetrical matrix whose entries on the main diagonal and all secondary diagonals are constant. A cyclic matrix is a persymmetric matrix whose entries are constant on all diagonals and are repeated cyclically .
Sum and product
The sum of two persymmetric matrices and again results in a persymmetric matrix, as are scalar multiples with . Since the zero matrix is trivially persymmetric, the persymmetric matrices form a sub-vector space in the matrix space .
![A + B](https://wikimedia.org/api/rest_v1/media/math/render/svg/4279cdbd3cb8ec4c3423065d9a7d83a82cfc89e3)
![A.](https://wikimedia.org/api/rest_v1/media/math/render/svg/7daff47fa58cdfd29dc333def748ff5fa4c923e3)
![cA](https://wikimedia.org/api/rest_v1/media/math/render/svg/aa433e0430d4d9fb7f97340b087950a77edb609d)
![K ^ {n \ times n}](https://wikimedia.org/api/rest_v1/media/math/render/svg/c10a4b78b51e6db58ee3f4b73b7e89eb589be5df)
The product of two persymmetric matrices results from
![A \ cdot B](https://wikimedia.org/api/rest_v1/media/math/render/svg/75a90e903f21f11a0f4ab3caca1e6943ba7a9849)
![JAB = A ^ TJB = A ^ TB ^ TJ = (BA) ^ TJ](https://wikimedia.org/api/rest_v1/media/math/render/svg/27103192e703c28b71636e8a1c5993fd02eecd4d)
a persymmetric matrix again if and only if the two matrices and commute .
![A.](https://wikimedia.org/api/rest_v1/media/math/render/svg/7daff47fa58cdfd29dc333def748ff5fa4c923e3)
Inverse
For the inverse of a persymmetric matrix, if it exists
![A ^ {- 1}](https://wikimedia.org/api/rest_v1/media/math/render/svg/83ba3a7118652cffd5de466dc439ee9184371d50)
-
.
The inverse of a regular persymmetric matrix is therefore again persymmetric.
See also
literature
- Gene Golub, Charles van Loan: Matrix Computations . JHU Press, 2013, ISBN 978-1-4214-0794-4 .
- Martin Hanke-Bourgeois: Fundamentals of Numerical Mathematics and Scientific Computing . Springer, 2008, ISBN 978-3-8348-0708-3 .
- Roger A. Horn, Charles R. Johnson: Matrix Analysis . Cambridge University Press, 2012, ISBN 978-0-521-83940-2 .
Individual evidence
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↑ Martin Hanke-Bourgeois: Fundamentals of numerical mathematics and scientific computing . Springer, 2008, p. 66 .
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^ Roger A. Horn, Charles Johnson: Matrix analysis . Cambridge University Press, 2013, pp. 36 .
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^ Gene Golub, Charles van Loan: Matrix Computations . JHU Press, 2013, p. 208 .