Abstract
Observability is a very useful concept for determining whether the dynamics of complicated systems can be correctly reconstructed from a single (univariate or multivariate) time series. When
the governing equations of dynamical systems are high-dimensional and/or rational, analytical computations
of observability coefficients produce large polynomial functions with a number of terms that become exponentially large with the dimension and the nature of the system. In order to overcome
this difficulty, we introduced here a new symbolic observability coefficient based on a symbolic computation of the determinant of the observability matrix. The computation of such coefficients
is straightforward and can be easily analytically carried out as demonstrated in this paper for a 5D rational system.
the governing equations of dynamical systems are high-dimensional and/or rational, analytical computations
of observability coefficients produce large polynomial functions with a number of terms that become exponentially large with the dimension and the nature of the system. In order to overcome
this difficulty, we introduced here a new symbolic observability coefficient based on a symbolic computation of the determinant of the observability matrix. The computation of such coefficients
is straightforward and can be easily analytically carried out as demonstrated in this paper for a 5D rational system.
| Original language | English |
|---|---|
| Article number | 062912 |
| Number of pages | 10 |
| Journal | Physical Review. E, Statistical, Nonlinear and Soft Matter Physics |
| Volume | 91 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 18 Jun 2015 |