Meta level tracking with stochastic grammar
The ability to learn about a stochastic process from noisy observations is fundamental to many applications. In order to track a dynamic process, the typical knowledge representation required is the state space model such as a linear Gauss Markov model, where efficient algorithms exists to perform s...
Main Author: | |
---|---|
Language: | English |
Published: |
University of British Columbia
2009
|
Online Access: | http://hdl.handle.net/2429/12263 |