A new random variable normalizing transformation with application to the GLRT
Document Type
Article
Date of Original Version
2-1-2018
Abstract
A means of converting a random variable into an approximate standard normal is described. It is an extension of the transformation inherent in the use of the exponential embedded family approach to multifamily likelihood ratio testing, which helps explain why the transformation employed corrects the deficiencies of the generalized likelihood ratio test.
Publication Title, e.g., Journal
IEEE Signal Processing Letters
Volume
25
Issue
2
Citation/Publisher Attribution
Kay, Steven, and Yazan Rawashdeh. "A new random variable normalizing transformation with application to the GLRT." IEEE Signal Processing Letters 25, 2 (2018): 189-193. doi: 10.1109/LSP.2017.2781235.
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