@article{elaa19,
author = {Eld\'en, L. and Ahmadi-Asl, S.},
title = {Solving bilinear tensor least squares problems and application to Hammerstein identification},
journal = {Numerical Linear Algebra with Applications},
volume = {26},
number = {2},
pages = {e2226},
keywords = {bilinear regression, bilinear tensor least squares problem, Hammerstein identification, Gauss–Newton-type method, separable, variable projection},
doi = {10.1002/nla.2226},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/nla.2226},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/nla.2226},
note = {e2226 nla.2226},
abstract = {Summary Bilinear tensor least squares problems occur in applications such as Hammerstein system identification and social network analysis. A linearly constrained problem of medium size is considered, and nonlinear least squares solvers of Gauss–Newton-type are applied to numerically solve it. The problem is separable, and the variable projection method can be used. Perturbation theory is presented and used to motivate the choice of constraint. Numerical experiments with Hammerstein models and random tensors are performed, comparing the different methods and showing that a variable projection method performs best.},,
year = {2019}
}