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MTE 712
Sensor Fusion
Sensor data and information fusion systems. Sensor modelling, including characterization of uncertainty. Sensor fusion approaches for estimation and decisions including weighted least squares, extended Kalman Filter, Dempster-
Shafer evidential reasoning, artificial neural networks; Outlier rejection; Spatial and temporal registration. Course project involving independent study of one aspect of sensor data fusion.
Weekly Contact: Lab: 1 hr. Lecture: 3 hrs.
GPA Weight: 1.00
Course Count: 1.00
Billing Units: 1
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