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Course
CIVIL-606: Inference for large-scale time series with application to sensor fusion
Summary
Large-scale time series analysis is performed by a new statistical tool that is superior to other estimators of complex state-space models. The identified stochastic dependences can be used for sensor fusion by Bayesian (e.g. Kalman) filtering or for studying changes in natural/biological phenomena.
Official source
Moodle Page
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