Eigenvalue of overlapping block matrix

In summary, The conversation discusses a problem with a specific matrix and how to obtain its eigenvalues analytically. The matrix has a specific block structure that can be used to find the eigenvectors. The conversation also mentions that the matrix is rank 3, meaning all but three of the eigenvalues are zero. The conversation also notes that the matrix is called a "name" in mathematics and the speaker is looking for inspiration in the mathematics matrix community.
  • #1
eegyan
1
0
I have got a problem in my research. For the following matrix,
a a a a a a b b b b
a a a a a a b b b b
a a a a a a b b b b
a a a a a a b b b b
a a a a a a a a a a
a a a a a a a a a a
b b b b a a a a a a
b b b b a a a a a a
b b b b a a a a a a
b b b b a a a a a a,
does anyone know how to obtain its eigenvalues analytically when the matrix size goes large? Is there any "name" for matrices just like this in mathmatics? I want to search for some inspiration in mathematics matrix community, but I even do not know what it is called in mathmatics. Thanks in advance.
 
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  • #2
Well the matrix is rank 3, so all but three of the eigenvalues are zero. We can use the block structure to find the eigenvectors, and hence the eigenvalues.

If there are x, y and z of each type of row, a vector with x ones then all zeros is an eigenvector, as is a vector with x zeros, y ones then z zeros, and so is a vector with x+y zeros followed by z ones
 

Related to Eigenvalue of overlapping block matrix

1. What is an eigenvalue of an overlapping block matrix?

An eigenvalue of an overlapping block matrix is a scalar value that represents the scaling factor of a vector when multiplied by the matrix. In other words, it is a value that satisfies the equation Ax = λx, where A is the overlapping block matrix, λ is the eigenvalue, and x is the eigenvector.

2. How is the eigenvalue of an overlapping block matrix calculated?

The eigenvalue of an overlapping block matrix can be calculated by solving the characteristic equation det(A-λI) = 0, where A is the matrix, λ is the eigenvalue, and I is the identity matrix. This equation will give multiple solutions, each representing a different eigenvalue of the matrix.

3. What is the significance of the eigenvalue of an overlapping block matrix?

The eigenvalue of an overlapping block matrix is significant because it provides information about the properties and behavior of the matrix. It can help determine the stability and convergence of numerical methods used to solve equations involving the matrix, and it is also useful in applications such as data compression and signal processing.

4. Can an eigenvalue of an overlapping block matrix be negative?

Yes, an eigenvalue of an overlapping block matrix can be negative. Eigenvalues can be positive, negative, or zero, and they can also be complex numbers. The sign of the eigenvalue can provide information about the direction and behavior of the vector when multiplied by the matrix.

5. How are eigenvalues of overlapping block matrices affected by changes in the matrix?

The eigenvalues of an overlapping block matrix can change if the matrix is modified in some way, such as by adding or subtracting rows or columns, or by multiplying by a scalar. However, the eigenvalues will remain the same if the matrix is simply multiplied by a non-zero constant. Changes in the matrix can also affect the eigenvectors associated with each eigenvalue.

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