Structured low-rank approximation for nonlinear matrices
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics
Link
https://link.springer.com/content/pdf/10.1007/s11075-022-01479-5.pdf
Reference33 articles.
1. Eckart, C., Young, G.: The approximation of one matrix by another one of lower rank. Psychometrika 1, 211–218 (1936). https://doi.org/10.1007/BF02288367
2. Markovsky, I.: Low-rank Approximation: Algorithms, Implementation, Applications, 2nd edn. Springer, Berlin (2019)
3. Chu, M.T., Funderlic, R.E., Plemmons, L.J.: Structured low rank approximation. Linear Algebra Its Appl. 366, 157–172 (2003). https://doi.org/10.1016/S0024-3795(02)00505-0
4. De Moor, B.: Total least squares for affinely structured matrices and the noisy realization problem. IEEE Trans. Signal Process. 42, 3104–3113 (1994). https://doi.org/10.1109/78.330370
5. Usevich, K., Markovsky, I.: Variable projection for affinely structured low-rank approximation in weighted 2-norms. J. Comput. Appl. Math. 272, 430–448 (2014). https://doi.org/10.1016/j.cam.2013.04.034
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