The Data Fusion and Analysis curricular unit aims to introduce the fundamental concepts related to the theory, design and implementation of data/information fusion from various sources, in various domains. The course covers several methodologies capable of combining data from several heterogeneous sources, in order to make inferences with application in decision support systems, clinical diagnosis, fault detection and others. The content is multidisciplinary, including topics such as time series analysis, state estimation, stratification, classification and data mining.
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Time series analysis, state estimation, stratification, classification and data mining. Kalman filters and Particle filters
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