[humanarity]

Hmm, good question. I'd say this would simply distribute the contribution of each window member along an exponential (rather than constant) trend. The terms in the mean vector would then be polynomials of the window members. Even if you lined up t_(x^n) weight with t_(x^m), it seems to me the other t_i filtered at exponential distances wouldn't line up. You'd could probably arrange it to get split on these nonidentical term weights, and maybe this could work as a (somewhat involved) method of feature selection that didn't degenerate to identical contributions. Interesting idea! - and maybe there's a few papers about it somewhere :)