Least Square Joint Diagonalization of Matrices under an Intrinsic Scale Constraint

Abstract. We present a new algorithm for approximate joint diagonalization of several symmetric matrices. While it is based on the classical least squares criterion, a novel intrinsic scale constraint leads to a simple and easily parallelizable algorithm, called LSDIC (Least squares Diagonalization under an Intrinsic Constraint). Numerical simulations show that the algorithm behaves well as compared to other approximate joint diagonalization algorithms.

• Type: Conference
• Year: 2009
• Where: IDA
• Authors: Dinh-Tuan Pham, Marco Congedo
• Keywords: Approximate Joint Diagonalization, IDA 2009, Information Management, Joint Diagonalization Algorithms, Least Squares Diagonalization