MEMS-cochlea: Dataset for publication

This is the dataset to the publication " Neuromorphic acoustic sensing using an adaptive microelectromechanical cochlea with integrated feedback" by Lenk et al. (DOI will follow soon). Explanation of data: 1.) 'MEMS cochlea response to natural sound' (dataset for fig 2 in publica...

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Bibliographische Detailangaben
1. Verfasser: Lenk, Claudia
Format: Dataset
Sprache:eng
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Zusammenfassung:This is the dataset to the publication " Neuromorphic acoustic sensing using an adaptive microelectromechanical cochlea with integrated feedback" by Lenk et al. (DOI will follow soon). Explanation of data: 1.) 'MEMS cochlea response to natural sound' (dataset for fig 2 in publication): In this dataset, the file "natural sound dateset" was used to drive a loudspeaker. Its given in wav-format. File named timeseries..." give the data of the response of two different sensors as well as a measurement microphone (named "input") to the wav-file. First column time in sec, second column sensor signal in V. Files named "powerspectra..." give the power spectra data of the three time series, first column frequency in Hz, second column power in absolute values not dB. 2.) 'Sensor response in dependence of feedback' (dataset for fig 3 in publication): The dataset includes the sensor signal amplitudes in mV (2nd column) as function of sound pressure amplitudes in Pa (1st column) in files with name starting "fig3a..." for different feedback strengths a_f given by the filename. Files, whose names start with "fig3b+c", give the gain (sensor amplitude active, i.e. a_f>0, divided by sensor amplitude passive, i.e. a_f=0) in the 2nd column as a function of the feedback strength a_f (1st column). In files named "fig3e_sensamp...", the sensor signal amplitude in V (2nd column) is given in dependence of the feedback strength a_f (1st column) for different driving voltages of the loudpseaker, given by the number after "loud" in the filename. If the filename says "negafnegDC", the feedback strength a_f is negativ. If it says "posafnegDC", the feedback strength was positive. The DC voltage of the feedback was always -200mV. From the dependence of sensor signal amplitude on the driving signal amplitude (both in mV), the sensitivity is extracted as the slope of the curve in mV/mV. The sensitvity is given in files, named "fig3e_sensitvity..." in the 2nd column as function of feedback strength a_f (first column). 3.) 'Comparison experiment vs model' (dataset for fig 4 in publication): These files give the values plotted in the graphs. The files, named "acrit..." contain the values of a_crit (feedback strength at bifurcation, 2nd column of file) as function of bias voltage u_DC in mV (first column of file) obtained either from experiment or from the formula (last equation in methods part). The file, named "sensitivity...", has the feedback strength a_f in the 1st column and the sensitivit
DOI:10.5281/zenodo.7640417