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

https://edu.epfl.ch/coursebook/en/inference-for-large-scale-time-series-with-application-to-sensor-fusion-CIVIL-606

Moodle Page

http://go.epfl.ch/CIVIL-606

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Ontological neighbourhood

Statistics

Statistical inference: Mathematical statistics

Instructors (2)

Related courses (122)

Related MOOCs (16)

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