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This compact, informal introduction for graduate students and advanced undergraduates draws together modern state estimation methods including non-linear Kalman filters, particle filters, and the related smoothing algorithms. Its practical and algorithmic approach assumes only modest mathematical prerequisites. End-of-chapter exercises include computational assignments, and Matlab code is available for download.
Subject: Mathematics & Statistics -> Mathematics -> Probability