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The book offers an in-depth exploration of Kalman filtering, detailing various mathematical theories and computational methods. It covers both direct and indirect algorithm derivations, addressing topics such as correlated noise, time-invariant systems, and nonlinear applications. The informal style and rigorous yet elementary mathematics make it accessible for self-study, requiring only a basic understanding of linear algebra and probability. With over 100 exercises and a new chapter on filtering communication networks, the text is designed to enhance practical knowledge and application in real-time scenarios.
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Kalman Filtering, Charles K. Chui, Guanrong Chen
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- 2017
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