Eigenvalues and eigenvectors of symbolic matrix
lambda = eig(A)
[V,D] = eig(A)
[V,D,P] = eig(A)
lambda = eig(vpa(A))
[V,D] = eig(vpa(A))
lambda = eig(
returns a symbolic vector
containing the eigenvalues of the square symbolic matrix A
)A
.
[V,D] = eig(
returns matrices V and D. The
columns of A
)V
present eigenvectors of A
. The diagonal
matrix D
contains eigenvalues. If the resulting V
has the
same size as A
, the matrix A
has a full set of linearly
independent eigenvectors that satisfy A*V = V*D
.
[V,D,P] = eig(
returns a vector of indices
A
)P
. The length of P
equals to the total number of linearly
independent eigenvectors, so that A*V = V*D(P,P)
.
lambda = eig(vpa(
returns
numeric eigenvalues using variable-precision arithmetic.A
))
[V,D] = eig(vpa(
also returns
numeric eigenvectors.A
))