On Total Least-Squares Adjustment with Constraints

By Burkhard Schaffrin, Y. Felus. 2005

49 citations recorded by the source corpus.

Subfields: Applied Mathematics, Artificial Intelligence, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/2e17ebdf3c6c70b3cc9ff212bcaaa935201391a1

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Applied Mathematics

1. X. Fang
2. Bofeng Li
3. Yunzhong Shen
4. Yi Chen
5. Guobin Chang
6. Y. Felus
7. Alireza Amiri-Simkooei
8. Burkhard Schaffrin

In Artificial Intelligence

1. X. Fang
2. Yunzhong Shen
3. Bofeng Li
4. Yi Chen
5. Devrim Akca
6. Armin Gruen
7. Burkhard Schaffrin
8. Y. Felus

In Environmental Engineering

1. X. Fang
2. Yunzhong Shen
3. Bofeng Li
4. Yi Chen
5. Devrim Akca
6. Armin Gruen
7. Y. Felus
8. Burkhard Schaffrin

Citations in the corpus

• An iterative solution of weighted total least-squares adjustment (2011, methodology): “…have been developed to solve the homoscedastic (Schaffrin et al. 2006; Schaffrin and Felus 2008), weighted (Van Huffel and Vandewalle 1989; Markovsky et al. 2006; Schaffrin and Wieser 2008), constrained (Schaffrin and Felus 2005; Schaffrin 2006) and regularized (Golub et al. 1999) TLS problems.”
• On the multivariate total least-squares approach to empirical coordinate transformations. Three algorithms (2008, methodology): “Such an algorithm was published in Schaffrin and Felus (2005) , for instance, but was not adapted to transformation problems so far.”
• A structured and constrained Total Least-Squares solution with cross-covariances (2013, background): “Schaffrin and Felus (2005) and Schaffrin (2006) presented the iterative linear fixed and stochastic constrained TLS solutions based on a fixed form solution, which is separately detailed in Schaffrin and Wieser (2008) specifically for their unconstrained TLS solution.”
• On non-combinatorial weighted total least squares with inequality constraints (2014, methodology): “It must be noted that in each iteration, the ECWTLS algorithm proposed by Fang (2014a) has a similar form to the algorithm proposed by Schaffrin and Felus (2005), which means that the matrix inversion and multiplications were implemented in the same dimension.”
• Weighted total least squares: necessary and sufficient conditions, fixed and random parameters (2013, methodology): “Schaffrin and Felus (2005, 2009) presented that the WTLS could be used as a promising tool to solve the constrained TLS problem.”
• Least squares 3D surface and curve matching (2005, methodology): “The TLS is a relatively new adjustment method of estimating parameters in linear models that include errors in all variables (Schaffrin and Felus, 2003).”