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physics.data-an2019★ 6 cited
A robust principal component analysis for outlier identification in messy microcalorimeter data
J. W. Fowler, B. K. Alpert, Y. -I. Joe +3
A principal component analysis (PCA) of clean microcalorimeter pulse records can be a first step beyond statistically optimal linear filtering of pulses towards a fully non-linear…
physics.data-an2016★ 11 cited
When "Optimal Filtering" Isn't
J. W. Fowler, B. K. Alpert, W. B. Doriese +8
The so-called "optimal filter" analysis of a microcalorimeter's x-ray pulses is statistically optimal only if all pulses have the same shape, regardless of energy. The shapes of pu…
physics.data-an2015★ 27 cited
Algorithms for Identification of Nearly-Coincident Events in Calorimetric Sensors
B. Alpert, E. Ferri, D. Bennett +9
For experiments with high arrival rates, reliable identification of nearly-coincident events can be crucial. For calorimetric measurements to directly measure the neutrino mass suc…