Data Unfolding with Wiener-SVD Method - INSPIRE

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Data Unfolding with Wiener-SVD Method

May 9, 2017

24 pages

Published in:

JINST 12 (2017) 10, P10002

Published: Oct 4, 2017

e-Print:

1705.03568 [physics.data-an]

DOI:

10.1088/1748-0221/12/10/P10002

Report number:

BNL-114378-2017-JA

View in:

ADS Abstract Service

reference search42 citations

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Abstract: (arXiv)

Data unfolding is a common analysis technique used in HEP data analysis. Inspired by the deconvolution technique in the digital signal processing, a new unfolding technique based on the SVD technique and the well-known Wiener filter is introduced. The Wiener-SVD unfolding approach achieves the unfolding by maximizing the signal to noise ratios in the effective frequency domain given expectations of signal and noise and is free from regularization parameter. Through a couple examples, the pros and cons of the Wiener-SVD approach as well as the nature of the unfolded results are discussed.

Note:

26 pages, 12 figures, match the accepted version by JINST

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