Matching of eigenvalues of 2 matrices

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Hello Everybody,
Suppose I have 2 matrices with same size: . is a slight change of in the form of: . I do eigenvalue analysis on both matrices:
lambda_1 = eig(A_1);
lambda_2 = eig(A_2);
and want to do a comparison between eigenvalues of each matrix. How can I find the matching eigenvalue for the original , i.e. how can I identify each eigenmode from to its equivalent in ?

Accepted Answer

Christine Tobler
Christine Tobler on 29 Apr 2019
With R2018a, there is a new function matchpairs which might be useful for this. Basically, it takes a matrix of similarities between two sets, and matches these sets up in pairs.
Here's an example:
>> X = randn(100);
>> d = eig(X);
>> d2 = eig(X + randn(100)*1e-2);
>> max(abs(d - d2))
ans =
17.9169
>> m = matchpairs(abs(d - d2.'), 1e-1); % The columns of m map the elements of d to those of d2
>> max(abs(d(m(:, 1)) - d2(m(:, 2))))
ans =
0.1569
The second input to matchpairs gives a cutoff: If two values have a difference larger than 1e-1, they would not be matched at all, and would show up as a new eigenvalue and a disappeared eigenvalues instead.

More Answers (1)

KSSV
KSSV on 29 Apr 2019
A1 = rand(2) ;
[v1,d1] = eig(A1) ;
Columns of v1 gives eigen vectors.........diagonal (diag(d1)) gives you eignvalues. To compare them use isequal. Or you may substract them and get the difference.
  5 Comments
KSSV
KSSV on 29 Apr 2019
So sort them and keep them in order.....
Omar Kamel
Omar Kamel on 29 Apr 2019
It is not about sorting the list. It is about matching of the eigenvalues and eigenvectors to their equivalent in the other system, to know if any eigenmodes appeared or another eigenmodes disappeared.

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