How Distributed Correntropy Makes Kalman Filtering Smarter
Kalman filtering is a powerful mathematical tool for estimating unknown system states from noisy data. By incorporating correntropy — a nonlinear similarity measure — distributed Kalman filters become more robust to noise and outliers.
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