Identification of nonlinear dynamical systems from chaotic time series
The thesis mainly focuses on the problem of nonlinear dynamical system identification from observed time series, which is one of the challenging topics in nonlinear time series analysis. The problem of nonlinear dynamical system identification is addressed in this thesis in three aspects: parameter...
محفوظ في:
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| التنسيق: | Theses and Dissertations |
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2008
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| الوصول للمادة أونلاين: | http://hdl.handle.net/10356/6551 |
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| المؤسسة: | Nanyang Technological University |
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sg-ntu-dr.10356-6551 |
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sg-ntu-dr.10356-65512023-03-11T16:55:01Z Identification of nonlinear dynamical systems from chaotic time series Lu, Fangfang. Xu, Daolin School of Mechanical and Aerospace Engineering DRNTU::Engineering::Mechanical engineering::Mechanics and dynamics The thesis mainly focuses on the problem of nonlinear dynamical system identification from observed time series, which is one of the challenging topics in nonlinear time series analysis. The problem of nonlinear dynamical system identification is addressed in this thesis in three aspects: parameter identification; estimation of parameters and unobserved trajectory components; determination of the optimal model structure. Doctor of Philosophy (MAE) 2008-09-17T11:17:49Z 2008-09-17T11:17:49Z 2006 2006 Thesis http://hdl.handle.net/10356/6551 Nanyang Technological University application/pdf |
| institution |
Nanyang Technological University |
| building |
NTU Library |
| continent |
Asia |
| country |
Singapore Singapore |
| content_provider |
NTU Library |
| collection |
DR-NTU |
| topic |
DRNTU::Engineering::Mechanical engineering::Mechanics and dynamics |
| spellingShingle |
DRNTU::Engineering::Mechanical engineering::Mechanics and dynamics Lu, Fangfang. Identification of nonlinear dynamical systems from chaotic time series |
| description |
The thesis mainly focuses on the problem of nonlinear dynamical system identification from observed time series, which is one of the challenging topics in nonlinear time series analysis. The problem of nonlinear dynamical system identification is addressed in this thesis in three aspects: parameter identification; estimation of parameters and unobserved trajectory components; determination of the optimal model structure. |
| author2 |
Xu, Daolin |
| author_facet |
Xu, Daolin Lu, Fangfang. |
| format |
Theses and Dissertations |
| author |
Lu, Fangfang. |
| author_sort |
Lu, Fangfang. |
| title |
Identification of nonlinear dynamical systems from chaotic time series |
| title_short |
Identification of nonlinear dynamical systems from chaotic time series |
| title_full |
Identification of nonlinear dynamical systems from chaotic time series |
| title_fullStr |
Identification of nonlinear dynamical systems from chaotic time series |
| title_full_unstemmed |
Identification of nonlinear dynamical systems from chaotic time series |
| title_sort |
identification of nonlinear dynamical systems from chaotic time series |
| publishDate |
2008 |
| url |
http://hdl.handle.net/10356/6551 |
| _version_ |
1761781539630219264 |