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In this article, we introduce the joint maximum a posteriori state path and parameter estimator (JME) for continuous-time systems described by stochastic differential equations (SDEs). This estimator can be applied to nonlinear systems with discrete-time (sampled) measurements with a wide range of measurement distributions. We also show that the minimum-energy state path and parameter estimator (MEE)...
Continuous–discrete models with dynamics described by stochastic differential equations are used in a wide variety of applications. For these systems, the maximum a posteriori (MAP) state path can be defined as the curves around which lie the infinitesimal tubes with greatest posterior probability, which can be found by maximizing a merit function built upon the Onsager–Machlup functional. A common...
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