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...
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| Language: | English |
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University of British Columbia
2009
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| Online Access: | http://hdl.handle.net/2429/12263 |