Zhou, B. B.Brent, Richard2015-12-080743-7315http://hdl.handle.net/1885/35928Jacobi-based algorithms have attracted attention as they have a high degree of potential parallelism and may be more accurate than QR-based algorithms. In this paper we discuss how to design efficient Jacobi-like algorithms for eigenvalue decomposition of a real normal matrix. We introduce a block Jacobi-like method. This method uses only real arithmetic and orthogonal similarity transformations and achieves ultimate quadratic convergence. A theoretical analysis is conducted and some experimental results are presented. CrownKeywords: Eigenvalue decomposition; Jacobi algorithm and QR algorithm; Normal matrix; Parallel computingAn efficient method for computing eigenvalues of a real normal matrix200310.1016/S0743-7315(03)00007-82015-12-08