Particle Filters for Random Set Models
Particle Filters for Random Set Models presents coverage of state estimation of stochastic dynamic systems from noisy measurements, specifically sequential Bayesian estimation and nonlinear or stochastic filtering. The class of solutions presented in this book is based� on the Monte Carlo statisti...
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| Format: | Electronic |
| Language: | English |
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New York, NY :
Springer New York : Imprint: Springer,
2013.
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| Online Access: | https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-1-4614-6316-0 |