摘要：AbstractOptimization problems arising in Optimum Experimental Design (OED) applications require repeated covariance matrix evaluations of the underlying Parameter Estimation (PE) problems. The complexity of this task grows quickly with the problem dimensions, especially when process noise is considered. In this paper, a Schur complement method is proposed to alleviate this problem by translating the covariance matrix evaluation into the solution of a sparse linear system and the inversion of a small-scale matrix. The method is used as a building block for the open-source software package casiopeia, a powerful and easy-to-use environment for OED and PE. The performance of the software and the proposed Schur complement method is assessed on a numerical example.
关键词：KeywordsInputexcitation designSoftware for system identification
