Brief paper: Maximum likelihood identification of noisy input-output models
Automatica (Journal of IFAC)
Overview of total least-squares methods
Signal Processing
Survey paper: Structured low-rank approximation and its applications
Automatica (Journal of IFAC)
Parameter estimation from noisy measurements
International Journal of Systems Science
High-performance numerical algorithms and software for structured total least squares
Journal of Computational and Applied Mathematics
Approximate low-rank factorization with structured factors
Computational Statistics & Data Analysis
Structured Total Maximum Likelihood: An Alternative to Structured Total Least Squares
SIAM Journal on Matrix Analysis and Applications
On weighted structured total least squares
LSSC'05 Proceedings of the 5th international conference on Large-Scale Scientific Computing
Software for weighted structured low-rank approximation
Journal of Computational and Applied Mathematics
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A structured total least squares problem is considered in which the extended data matrix is partitioned into blocks and each of the blocks is block-Toeplitz/Hankel structured, unstructured, or exact. An equivalent optimization problem is derived and its properties are established. The special structure of the equivalent problem enables us to improve the computational efficiency of the numerical solution methods. By exploiting the structure, the computational complexity of the algorithms (local optimization methods) per iteration is linear in the sample size. Application of the method for system identification and for model reduction is illustrated by simulation examples.