The estimation of the measurand in the analysis of dynamic measurements typically corresponds to a deconvolution problem. Therefore, a digital filter can be designed whose input is the measured system output signal and whose output is an estimate of the measurand. The package PyDynamic.model_estimation implements methods for the design of such filters given an array of frequency response values or the reciprocal of frequency response values with associated uncertainties for the measurement system.
The package PyDynamic.model_estimation also contains a function for the identification of transfer function models.
The package consists of the following modules:
PyDynamic.model_estimation.fit_filter: least-squares fit to a given complex frequency response or its reciprocalPyDynamic.model_estimation.fit_transfer: identification of transfer function models
PyDynamic.model_estimation.fit_filter
PyDynamic.model_estimation.fit_transfer