Data Unfolding with Wiener-SVD Method
Data Analysis, Statistics and Probability
2017-10-06 v2 High Energy Physics - Experiment
Nuclear Experiment
Abstract
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.
Keywords
Cite
@article{arxiv.1705.03568,
title = {Data Unfolding with Wiener-SVD Method},
author = {W. Tang and X. Li and X. Qian and H. Wei and C. Zhang},
journal= {arXiv preprint arXiv:1705.03568},
year = {2017}
}
Comments
26 pages, 12 figures, match the accepted version by JINST