Abstract
Behaviours provide an elegant, parameter free characterization of deterministic systems. We discuss a possible application of behaviours in the approximation of stochastic systems. This can be seen as an extension to the dynamic case of the well-known static factor analysis model. An essential difference is that we see modelling primarily as a matter of process approximation, not as a method to recover the true data generating process. In particular we see 'noise properties' as a kind of prior model assumption that can be compared with the resulting quality of the process approximation.
| Original language | English |
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| Journal | Proceedings of the IEEE Conference on Decision and Control |
| Publication status | Published - 1996 |
| Externally published | Yes |
| Event | Proceedings of the 1996 35th IEEE Conference on Decision and Control. Part 3 (of 4) - Kobe, Jpn Duration: 11 Dec 1996 → 13 Dec 1996 |