TY - DATA T1 - Parallel Wiener-Hammerstein Time Series PY - 2020/09/15 AU - Maarten Schoukens UR - https://data.4tu.nl/articles/dataset/Parallel_Wiener-Hammerstein_Time_Series/12950081/1 DO - 10.4121/12950081.v1 KW - Wiener-Hammerstein KW - System Identification KW - Nonlinear KW - Machine Learning KW - Dynamic System KW - Electronic Circuit KW - time series N2 -
A Parallel Wiener-Hammerstein system is a nonlinear dynamical system obtained by connecting multiple Wiener-Hammerstein systems in parallel. Each parallel branch contains a static nonlinearity that is sandwiched in between two linear time-invariant (LTI) blocks. The presence of the two LTI blocks, and the parallel branches results in a problem that is harder to identify. The LTI blocks are realized as active filters while the static nonlinearity is implemented as a diode-resistor electronic circuit.
The provided data was part of a previously published Automatica paper available online at Sciencedirect or as an ArXiv preprint. The Parallel Wiener-Hammerstein system, the measurement setup, and the input signals used are detailed in Section 10 of the aforementioned paper.
This zip-file contains multiple measured input-output time series: a multisine estimation/validation data set, and a multisine and increasing-amplitude test data set. The data is available in the .csv and .mat file format.
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