Home

m×morthogonale

An m-by-m orthogonal matrix is a real square matrix A ∈ R^{m×m} that satisfies A^T A = A A^T = I_m, where A^T is the transpose and I_m is the identity matrix. This condition is equivalent to A^T = A^{-1}, so orthogonal matrices preserve inner products and norms: for any vectors x, y in R^m, (Ax)·(Ay) = x·y and ||Ax|| = ||x||.

Orthogonal matrices form the group O(m) under matrix multiplication; the subgroup of determinant +1, denoted SO(m),

Real eigenvalues of an orthogonal matrix are restricted to ±1, while generally the eigenvalues lie on the

Typical examples include the identity I_m, rotation and reflection matrices, and permutation matrices. Because A is

Applications of orthogonal matrices are widespread: in numerical linear algebra they underlie Gram–Schmidt processes and QR

As a Lie group, O(m) has dimension m(m−1)/2, and its determinant-one subgroup SO(m) inherits the same dimension.

consists
of
orientation-preserving
orthogonal
transformations.
unit
circle
in
the
complex
plane.
Over
the
real
numbers,
A
need
not
be
diagonalizable,
but
over
the
complex
field
it
is
diagonalizable
with
eigenvalues
of
modulus
1.
orthogonal,
its
inverse
is
A^T
and
its
rank
is
full.
decompositions;
in
computer
graphics
they
represent
rotations
and
reflections
in
three-dimensional
space;
in
statistics
and
signal
processing
they
appear
in
data
whitening
and
multivariate
analysis.