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@@ -19,12 +19,11 @@ After installing the Python environment, install the required packages using "pi
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Two separate folders contain multiple scripts; for the analysis of in-vitro characterizations (folder "in-vitro") and for the analysis of signals in-vivo (folder "in-vivo") using probe labeled
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Two separate folders contain multiple scripts; for the analysis of in-vitro characterizations (folder "in-vitro") and for the analysis of signals in-vivo (folder "in-vivo") using probe labeled
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as B12784O18-T3.
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as B12784O18-T3.
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-For the in-vitro data, the demo includes a python dictionary exported as a .h5 file (named "GmIrmsUrmsIds10Probe.h5"), which includes the summary data from the characterization of all ECoG arrays.
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-The script which generates and exports this dictionary has also been included ("CalcGM_Noise_LMU_multipleFiles.py"), but not all the raw data required to run this script has been included.
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-The script "PlotStatistics.py" can be executed as part of this demo, which produces the graphs in Fig.2 of the present article.
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+For the in-vitro data, the demo includes a python dictionary exported as a .h5 file (named "GmIrmsUrmsIds10Probe_2.h5"), which includes the summary data from the characterization of all ECoG arrays.
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+The script which generates and exports this dictionary has also been included ("CalcGM_Noise_LMU_multipleFiles.py").
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+The script "PlotStatistics.py" produces the graphs in Fig.2 of the present article.
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A simplified version of "CalcGM_Noise_LMU_multipleFiles.py" named "CalcGM_Noise_LMU.py", can be found which does the same calculations for only 1 characterization.
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A simplified version of "CalcGM_Noise_LMU_multipleFiles.py" named "CalcGM_Noise_LMU.py", can be found which does the same calculations for only 1 characterization.
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This script has been used to generate the Urms maps presented in Fig. 2. The bandwidth of noise integration was changed to produce the different graphs for (1-10 Hz and 20-200 Hz).
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This script has been used to generate the Urms maps presented in Fig. 2. The bandwidth of noise integration was changed to produce the different graphs for (1-10 Hz and 20-200 Hz).
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-A 1mVpk 10 Hz signal was applied at the gate in order to characterize the transconductance (Gm) of the g-SGFETs. In order to characterize the Irms noise without this contribution,
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-the signal was integrated in the range from 1.9Hz to 1.9sqrt(10) Hz and the result multiplied by a factor of sqrt(2) in order to calculate the approximate rms noise in the 1-10Hz. Expect a runing time in the order of 10 minutes.
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+A 1mVpk 10 Hz signal was applied at the gate in order to characterize the transconductance (Gm) of the g-SGFETs.
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In order to calculate the Urms map in the 0.05-0.5Hz band shown in Fig.2, a long recording at the optimal bias was taken, which is analyzed by the script "LongRec.py" to produce the plots in Fig. 2.
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In order to calculate the Urms map in the 0.05-0.5Hz band shown in Fig.2, a long recording at the optimal bias was taken, which is analyzed by the script "LongRec.py" to produce the plots in Fig. 2.
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Expect a runing time in the order of 10 minutes.
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Expect a runing time in the order of 10 minutes.
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