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 - <p>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.</p><p><br></p><p>The provided data was part of a previously published Automatica paper available online at <a target="_blank">Sciencedirect</a> or as an <a target="_blank">ArXiv preprint</a>. The Parallel Wiener-Hammerstein system, the measurement setup, and the input signals used are detailed in Section 10 of the aforementioned paper. </p><p><br></p><p>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.</p>
ER -