Analysis of Structured Low Rank Approximation as an Optimization Problem

@article{Gillard2011AnalysisOS,
  title={Analysis of Structured Low Rank Approximation as an Optimization Problem},
  author={Jonathan Gillard and Anatoly A. Zhigljavsky},
  journal={Informatica, Lith. Acad. Sci.},
  year={2011},
  volume={22},
  pages={489-505}
}
In this paper, we consider the so-called structured low rank approximation (SLRA) problem as a problem of optimization on the set of either matrices or vectors. Briefly, SLRA is defined as follows. Given an initial matrix with a certain structure (for example, Hankel), the aim is to find a matrix of specified lower rank that approximates this initial matrix, whilst maintaining the initial structure. We demonstrate that the optimization problem arising is typically very difficult; in particular… CONTINUE READING
Highly Cited
This paper has 21 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 13 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 25 references

Analysis of Structured Low Rank Approximation as an Optimization Problem

  • I. Markovsky, J. C. Willems, S. Van Huffel, B. De Moor
  • 2006
1 Excerpt

Similar Papers

Loading similar papers…