A Groebner basis approach to solve a rank minimization problem arising in 2D-identification
A Groebner basis approach to solve a rank minimization problem arising in 2D-identification
The problem of state-space modelling of 2D-trajectories from exponential data can
be solved using a duality approach. Finding a minimal complexity model, i.e. one having the minimal number of state variables among those unfalsified by the data, can be transformed to a rank-minimization problem involving constant matrices computed from the data. We illustrate a Groebner basis approach to solve such problem.
1834-1839
Rapisarda, Paolo
79efc3b0-a7c6-4ca7-a7f8-de5770a4281b
Rapisarda, Paolo
79efc3b0-a7c6-4ca7-a7f8-de5770a4281b
Rapisarda, Paolo
(2017)
A Groebner basis approach to solve a rank minimization problem arising in 2D-identification.
IFAC-PapersOnLine, 50 (1), .
(doi:10.1016/j.ifacol.2017.08.190).
Abstract
The problem of state-space modelling of 2D-trajectories from exponential data can
be solved using a duality approach. Finding a minimal complexity model, i.e. one having the minimal number of state variables among those unfalsified by the data, can be transformed to a rank-minimization problem involving constant matrices computed from the data. We illustrate a Groebner basis approach to solve such problem.
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Accepted/In Press date: 3 April 2017
e-pub ahead of print date: 18 October 2017
Venue - Dates:
20th IFAC World congress, , Toulouse, France, 2017-07-09 - 2017-07-14
Identifiers
Local EPrints ID: 412480
URI: http://eprints.soton.ac.uk/id/eprint/412480
ISSN: 2405-8963
PURE UUID: 5f84c287-36c9-4f40-832e-6bcc8d24a587
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Date deposited: 17 Jul 2017 13:58
Last modified: 15 Mar 2024 16:56
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Author:
Paolo Rapisarda
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