High-performance numerical algorithms and software for structured total least squares

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We present a software package for structured total least-squares approximation problems. The allowed structures in the data matrix are block-Toeplitz, block-Hankel, unstructured, and exact. Combination of blocks with these structures can be specified. The computational complexity of the algorithms is O(m), where m is the sample size. We show simulation examples with different approximation problems. Application of the method for multivariable system identification is illustrated on examples from the database for identification of systems DAISY.

论文关键词:Parameter estimation,Structured total least squares,Deconvolution,System identification,Numerical linear algebra

论文评审过程:Received 15 June 2004, Accepted 2 November 2004, Available online 16 December 2004.

论文官网地址:https://doi.org/10.1016/j.cam.2004.11.003