Markov Approximations: The Characterization of Undermodeling Errors
This thesis is concerned with characterizing the quality of Hidden Markov modeling when learning from limited data. It introduces a new perspective on different sources of errors to describe the impact of undermodeling. Our view is that modeling errors can be decomposed into two primary sources of e...
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| Format: | Others |
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BYU ScholarsArchive
2006
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| Online Access: | https://scholarsarchive.byu.edu/etd/517 https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=1516&context=etd |