@inbook{67b5617b7bc143359196c15deb4cd241,
title = "Correntropy for random variables: Properties and applications in statistical inference",
abstract = "Similarity is a key concept to quantify temporal signals or static measurements. Similarity is difficult to define mathematically, however, one never really thinks too much about this difficulty and naturally translates similarity by correlation. This is one more example of how engrained second-order moment descriptors of the probability density function really are in scientific thinking. Successful engineering or pattern recognition solutions from these methodologies rely heavily on the Gaussianity and linearity assumptions, exactly for the same reasons discussed in Chapter 3.",
author = "Weifeng Liu and Puskal Pokharel and Jianwu Xu and Sohan Seth",
year = "2010",
doi = "10.1007/978-1-4419-1570-2_10",
language = "English",
isbn = "978-1-4419-1569-6",
series = "Information Science and Statistics",
publisher = "Springer",
pages = "385--413",
booktitle = "Information Theoretic Learning",
address = "United Kingdom",
}