Titlebook: Kalman Filtering; with Real-Time Appli Charles K. Chui,Guanrong Chen Textbook 20094th edition Springer-Verlag GmbH Germany, part of Springe

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Sequential and Square-Root Algorithms,mary concern of the Kalman filter is its real-time capability, it is of utmost importance to be able to compute . preferably without directly inverting a matrix at each time instant, and/or to perform efficiently and accurately a modified operation, whether it would involve matrix inversions or not.

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Decoupling of Filtering Equations,l-time. However, if the state vector has a very high dimension ., and only a few components are of interest, this filter gives an abundance of useless information, an elimination of which should improve the efficiency of the filtering process. A decoupling method is introduced in this chapter for th

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Kalman Filtering for Interval Systems,ng algorithm cannot be directly applied. In this case, robust Kalman filtering that has the ability of handling uncertainty is needed. In this chapter we introduce one of such robust Kalman filtering algorithms.

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Wavelet Kalman Filtering,ng performed in the time domain. Among them, perhaps the most exciting ones are wavelet algorithms, which are useful tools for multichannel signal processing (e.g., estimation or filtering) and multiresolution signal analysis. This chapter is devoted to introduce this effective technique of wavelet

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Notes, real-time applications. No attempt was made to cover all the rudiment of the theory, and only a small sample of its applications has been included. There are many texts in the literature that were written for different purposes, including Anderson and Moore (1979), Balakrishnan (1984,87), Brammer a