ROC Curve Analysis
ROC Curve Analysis
(OP)
I'm trying to discern the SNR (in dB) from a set of ROC curves. I have noise and signal plus noise pdf's from which I generate a series or ROC curves and from this ROC plot I want to reformat the x (probability of false alarm) and y (probability of detection) axis so that the ROC curves themselves are plotted as linear functions. This is similar to plotting exponential functions on log-log graphs. I guess my question is how to I pass the x and y data through their respective inverse functions so that when I plot them I get linear functions? From this plot I could then by inspection find the distance from each and associate this with some measurable SNR.





RE: ROC Curve Analysis
Dan - Owner

http://www.Hi-TecDesigns.com
RE: ROC Curve Analysis
If you would like to know the origin of this problem (while its application is fairly vast) or more specifics, please feel free to pm me.
RE: ROC Curve Analysis
RE: ROC Curve Analysis
This website shows ROC plots for normal or Guassian distributions:
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RE: ROC Curve Analysis
You can get SNR without that though as you have the noise PDF.
To my understanding the SNR is independent of the detection method and the ROC. The Receiver Operating Curve is mainly a function of the detection method.
It's compexicated thought maybe i got it backward.
RE: ROC Curve Analysis
You seem to be right again that SNR is independent of the detection method, detection threshold and ROC plot and this makes sense seeing that two different SNR ratios could essentially produce the same ROC plot given the right circumstances. I'm trying to reproduce the following graph so that I can graphically deduce the SNR difference between curves. This is still somewhat foggy but thanks for the points.
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