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The most commonly used algorithm in real-time control systems, such as the control of the movement of vehicles (especially, automobiles, ships, aircraft, and spacecraft), robotic motion planning and control and so on, is the Kalman filter. The limitation of this algorithm is that it assumes that the process is affected only by random zero-mean white Gaussian noises. But when measurement processes...
A still open issue, in uncertainty evaluation, is that of asymmetrical distributions of the values that can be attributed to the measurand. This problem becomes generally not negligible when the measurement function is highly non-linear. In this case the law of uncertainty propagation suggested by the GUM is not correct any longer, and only Monte Carlo simulations can be used to obtain such distributions...
Conditional probability distributions and Bayes' theorem are an important and powerful tool in measurement, whenever a priori information about the measurand is available. It is well-known that the measurement result and associated uncertainty (a posteriori information) can be used to revise the a priori information and, hopefully, decrease its uncertainty. This tool can be used only if both a priori...
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