In this chapter more general models are considered. We use again the same reference measure methods. Both nonlinear with nonadditive noise and linear dynamics are considered. In Section 5.7 the results are extended to a parameter estimation problem. In this case the same noise enters the signal and observations. In Section 5.8, an abstract formulation is given in terms of transition densities. Finally, in Section 5.9 we discuss a correlated noise case, where the noise in the observations appears in the state dynamics as well.
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© 1995 Springer Science+Business Media, LLC
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(1995). A General Recursive Filter. In: Hidden Markov Models. Stochastic Modelling and Applied Probability, vol 29. Springer, New York, NY. https://doi.org/10.1007/978-0-387-84854-9_5
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DOI: https://doi.org/10.1007/978-0-387-84854-9_5
Publisher Name: Springer, New York, NY
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