J. O. Coleman

Generalize Higher-Order Moments in Independent Component Analysis
J. O. Coleman
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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Presented at the IEEE 2000 International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2000), Istanbul, Turkey, June 5-9, 2000.