Name
Title | ||
|---|---|---|
An Approach to Sparse Continuous-time System Identification from Unevenly Sampled Data. |
Abstract | ||
|---|---|---|
In this work, we address the problem of identifying sparse continuous-time dynamical systems when the spacing between successive samples (the sampling period) is not constant over time. The proposed approach combines the leave-one-sample-out cross-validation error trick from machine learning with an iterative subset growth method to select the subset of basis functions that governs the dynamics of the system. The least-squares solution using only the selected subset of basis functions is then used. The approach is illustrated on two examples: a 6-node feedback ring and the Van der Pol oscillator. |
Year | Venue | Field |
|---|---|---|
2018 | arXiv: Systems and Control | Mathematical optimization,Continuous time system,Sampling (signal processing),Algorithm,Van der Pol oscillator,Dynamical systems theory,Basis function,Mathematics |
DocType | Volume | Citations |
Journal | abs/1802.10348 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rui Teixeira Ribeiro | 1 | 0 | 0.34 |
| Alexandre Mauroy | 2 | 59 | 8.21 |
| Goncalves, J. | 3 | 404 | 42.24 |