| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 695436 | Automatica | 2014 | 8 Pages |
Abstract
We present an elimination theory-based method for solving equality-constrained multivariable polynomial least-squares problems in system identification. While most algorithms in elimination theory rely upon Groebner bases and symbolic multivariable polynomial division algorithms, we present an algorithm which is based on computing the nullspace of a large sparse matrix and the zeros of a scalar, univariate polynomial.
Related Topics
Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
Matthew S. Hölzel, Dennis S. Bernstein,