Pseudorandom maximum length signal design with bias compensation least squares estimation for system identification
The effect of input and output noise towards the identification of the best linear approximation of a system is investigated. This leads to the problem of errors-in-variables (EIV). The effectiveness of one particular EIV method, namely the bias compensation least squares estimation method, is analy...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
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2007
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| Online Access: | http://shdl.mmu.edu.my/3275/ |
| _version_ | 1848790282444734464 |
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| author | Foo, Mathias Fui Lin Tang, Ai Hui Basu, Kartik Prasad |
| author_facet | Foo, Mathias Fui Lin Tang, Ai Hui Basu, Kartik Prasad |
| author_sort | Foo, Mathias Fui Lin |
| building | MMU Institutional Repository |
| collection | Online Access |
| description | The effect of input and output noise towards the identification of the best linear approximation of a system is investigated. This leads to the problem of errors-in-variables (EIV). The effectiveness of one particular EIV method, namely the bias compensation least squares estimation method, is analyzed, with simulations carried out on a first order bilinear system. It is shown that the use of perturbation signals with carefully selected harmonic properties can lead to significant improvements in the estimation of the best linear approximation of the system. In particular, a spectrum that is sparser but having a larger magnitude at the nonzero harmonics is found to be more robust towards the effect of noise. |
| first_indexed | 2025-11-14T18:10:08Z |
| format | Conference or Workshop Item |
| id | mmu-3275 |
| institution | Multimedia University |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:10:08Z |
| publishDate | 2007 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | mmu-32752011-10-18T01:38:01Z http://shdl.mmu.edu.my/3275/ Pseudorandom maximum length signal design with bias compensation least squares estimation for system identification Foo, Mathias Fui Lin Tang, Ai Hui Basu, Kartik Prasad T Technology (General) QA75.5-76.95 Electronic computers. Computer science The effect of input and output noise towards the identification of the best linear approximation of a system is investigated. This leads to the problem of errors-in-variables (EIV). The effectiveness of one particular EIV method, namely the bias compensation least squares estimation method, is analyzed, with simulations carried out on a first order bilinear system. It is shown that the use of perturbation signals with carefully selected harmonic properties can lead to significant improvements in the estimation of the best linear approximation of the system. In particular, a spectrum that is sparser but having a larger magnitude at the nonzero harmonics is found to be more robust towards the effect of noise. 2007-05 Conference or Workshop Item NonPeerReviewed Foo, Mathias Fui Lin and Tang, Ai Hui and Basu, Kartik Prasad (2007) Pseudorandom maximum length signal design with bias compensation least squares estimation for system identification. In: 24th IEEE Instrumentation and Measurement Technology Conference, 01-03 MAY 2007, Warsaw, POLAND. http://apps.webofknowledge.com/full_record.do?product=WOS&search_mode=GeneralSearch&qid=1&SID=Q2B3J83BDN3nFOLpEAc&page=127&doc=1263 |
| spellingShingle | T Technology (General) QA75.5-76.95 Electronic computers. Computer science Foo, Mathias Fui Lin Tang, Ai Hui Basu, Kartik Prasad Pseudorandom maximum length signal design with bias compensation least squares estimation for system identification |
| title | Pseudorandom maximum length signal design with bias compensation least squares estimation for system identification |
| title_full | Pseudorandom maximum length signal design with bias compensation least squares estimation for system identification |
| title_fullStr | Pseudorandom maximum length signal design with bias compensation least squares estimation for system identification |
| title_full_unstemmed | Pseudorandom maximum length signal design with bias compensation least squares estimation for system identification |
| title_short | Pseudorandom maximum length signal design with bias compensation least squares estimation for system identification |
| title_sort | pseudorandom maximum length signal design with bias compensation least squares estimation for system identification |
| topic | T Technology (General) QA75.5-76.95 Electronic computers. Computer science |
| url | http://shdl.mmu.edu.my/3275/ http://shdl.mmu.edu.my/3275/ |