Jacobi-like algorithms for eigenvalue decomposition of a real normal matrix using real arithmetic

In this paper, we introduce a method for designing efficient Jacobi-like algorithms for eigenvalue decomposition of a real normal matrix. The algorithms use only real arithmetic and achieve ultimate quadratic convergence. A theoretical analysis is conducted and some experimental results are presented.