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The method described in this paper is about separating signal (trend) from noise in a set of measured bivariate data when there is no mathematical model for that signal. A computer program called spline2 implements the algorithm, which the authors apply to laboratory and real-world example problems.
The difficulty for accurate determination of the angles of arrival (AOA) of signals arises from the optimization of likelihood functions of high dimension. Usually, a gradient-based technique is employed to find the optimum of the function. However, this method requires heavy computational work and the differentiability of the likelihood function. This paper presents two gradient-free methods: One...
This paper addresses the lack of robustness in the design of a classic self-tuning controller (STC); in particular the poor performance demonstrated if the time delay of the process is time varying. To avoid these problems, the implementation of a novel practical self-tuning controller (PSTC) is described. The PSTC employs plant excitation with a PRBS to ensure good model estimates, a process monitor...
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