Title
Solving bilinear tensor least squares problems and application to Hammerstein identification.
Abstract
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
DOI
Venue
2019
10.1002/nla.2226
NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS
Keywords
Field
DocType
bilinear regression,bilinear tensor least squares problem,Hammerstein identification,Gauss-Newton-type method,separable,variable projection
Least squares,Applied mathematics,Mathematical optimization,Tensor,Separable space,System identification,Mathematics,Bilinear interpolation
Journal
Volume
Issue
ISSN
26.0
2.0
1070-5325
Citations 
PageRank 
References 
0
0.34
7
Authors
2
Name
Order
Citations
PageRank
Lars Eldén119122.70
Salman Ahmadi-Asl282.49