MET nonlinear

This dataset comprises a collection of CSV files containing paired time-series measurements essential for nonlinear compensation research in electrochemical seismometers (MET). Each CSV file, named according to specific magnitude-frequency combinations (magX_freqY.csv), contains two columns: 'origin' representing the original system response and 'target' representing the desired compensated output. The dataset systematically captures system behavior across multiple excitation magnitudes and frequencies, providing a comprehensive basis for analyzing frequency-dependent nonlinear characteristics. These paired measurements enable researchers to develop and validate algorithms for nonlinear compensation, with particular emphasis on improving linearity across varying input conditions. The structured organization by magnitude and frequency parameters facilitates targeted analysis of system behavior under specific operating conditions, making this dataset valuable for developing advanced signal processing techniques and machine learning models aimed at enhancing measurement accuracy in sensor systems experiencing nonlinear distortion.