Summary

Description

<p>Ensemble Detection is both a measurement technique and analysis tool. Like a prism that separates light into spectral bands, an ensemble detector mixes a signal with noise references that span a range of noise powers that produce multiple realizations that comprise an ensemble data set. The resulting ensemble data set represents a comprehensive stochastic description of the signal that is admissible to statistical analysis not otherwise possible with a single realization. Ensemble data sets provide time-varying probability distribution functions from which time varying statistics can be derived. The linear relationship between the reference mean and standard deviation provides a way to discriminate changes in the process mean from changes in the spread of the process’ probability distribution. Why is this important? Distinguishing between a mean state change and natural variability is a problem that spans multiple scientific disciplines. One important application is discriminating between climate change and natural variability of extreme weather events.</p>