A new structure-preserving method for dual quaternion Hermitian eigenvalue problems

Abstract

Dual quaternion matrix decompositions have played a crucial role in fields such as formation control and image processing in recent years. In this paper, we present an eigenvalue decomposition algorithm for dual quaternion Hermitian matrices. The proposed algorithm is founded on the structure-preserving tridiagonalization of the dual matrix representation of dual quaternion Hermitian matrices through the application of orthogonal matrices. Owing to the utilization of orthogonal transformations, the algorithm exhibits numerical stability. Numerical experiments are provided to illustrate the efficiency of the structure-preserving algorithm.