- TITLE:
-
Generalize Higher-Order Moments
in Independent Component Analysis
- AUTHORS:
- J. O. Coleman
- ABSTRACT:
- In independent component analysis (ICA),
random-variable independence is often equated with
factorization of the joint moments, expectations of
products of powers. This paper shows that many
nonpower functions are equally useful: if E[f(X)g(Y)]
factors into E[f(X)]E[g(Y)] for every f and g from an
independence class, then random variables X and Y are
independent. Examples of and sufficient conditions
for independence classes are presented for bounded
random variables.
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- STATUS:
- Presented at the
IEEE 2000 International Conference on
Acoustics, Speech, and Signal Processing
(ICASSP 2000), Istanbul, Turkey, June 5-9, 2000.