Online Public Access Catalogue (OPAC)
Library,Documentation and Information Science Division

“A research journal serves that narrow

borderland which separates the known from the unknown”

-P.C.Mahalanobis


Kalman filtering :



xvii, 617 p. : illustrations ; 24 cm. Content notes : 1. Introduction --
2. Linear dynamic systems --
3. Probability and expectancy --
4. Random processes --
5. Linear optimal filters and predictors --
6. Optimal smoothers --
7. Implementation methods --
8. Nonlinear approximations --
9. Practical considerations --
10. Applications to navigation --
Appendix A: software --
Index. MATLAB. Kalman-Filter.

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