Learning probabilistic models of dynamical phenomena using particle filters
Dynamical behavior can be seen in many real-life phenomena, typically as a dependence over time. This thesis studies and develops methods and probabilistic models for statistical learning of such dynamical phenomena. A probabilistic model is a mathematical model expressed using probability theory. S...
| Main Author: | |
|---|---|
| Format: | Others |
| Language: | English |
| Published: |
Uppsala universitet, Avdelningen för systemteknik
2016
|
| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-311585 |