Abstract
The multilinear least-squares (MLLS) problem is an extension of the linear least-squares problem. The difference is that a multilinear operator is used in place of a matrix-vector product. The MLLS is typically a large-scale problem characterized by a large number of local minimizers. It originates, for instance, from the design of filter networks. We present a global search strategy that allows for moving from one local minimizer to a better one. The efficiency of this strategy is illustrated by the results of numerical experiments performed for some problems related to the design of filter networks.
Recommended Citation
Andersson, Mats; Burdakov, Oleg; Knutsson, Hans; and Zikrin, Spartak
(2012)
Global Search Strategies for Solving Multilinear Least-Squares Problems,
Sultan Qaboos University Journal For Science: Vol. 17:
Iss.
1, 12-21.
DOI: https://doi.org/10.24200/squjs.vol17iss1pp12-21
Available at:
https://squjs.squ.edu.om/squjs/vol17/iss1/10