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Identification of continuous-time models

机译:识别连续时间模型

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The problem of estimating the transfer function of a continuous-time dynamic system in the presence of colored noise is considered. An operator transformation that allows for keeping a continuous-time parametrization is introduced; the parameter estimation can be made by means of a discrete-time maximum-likelihood algorithm. A comparison is made between the performance of the new method in comparison with a standard identification of an ARMAX (autoregressive moving-average with exogeneous input) model. The method is useful in cases where it is important to estimate the coefficients of a continuous-time transfer function and to maintain a physical interpretation of the transfer function results.
机译:考虑了在存在着色噪声存在下连续时间动态系统的传递函数的问题。 介绍了允许保持连续时间参数化的操作员变换; 可以通过离散时间最大似然算法进行参数估计。 与ARMAX的标准识别相比,新方法的性能之间进行了比较(自向进口的进入)模型的标准识别。 该方法在估计连续时间传递函数的系数并保持转移函数结果的物理解释是重要的情况下是有用的。

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