Computing Similarity of Square Matrices by Eigenconjugation

In computer sciences, matrices are widely used for representing different kinds of information. Measuring similarity among square matrices is an interesting open problem in computer sciences. Furthermore, eigenvalues and eigenvectors are a powerful way for representing and characterizing square matrices. In this paper we introduce a new similarity measure among two square data matrices of the same class; the idea is based on evaluating the effect of conjugate the eigenvalues and eigenvectors of one matrix with the other matrix, and vice versa. Some experimental results are showed in order to analyze and exemplify the Eigenconjugation as an approach for the problem of similarity of matrices.