Publication Date
4-1-2021
Abstract
As a system becomes more complex, at first, its description and analysis becomes more complicated. However, a further increase in the system's complexity often makes this analysis simpler. A classical example is Central Limit Theorem: when we have a few independent sources of uncertainty, the resulting uncertainty is very difficult to describe, but as the number of such sources increases, the resulting distribution get close to an easy-to-analyze normal one -- and indeed, normal distributions are ubiquitous. We show that such limit theorems often make analysis of complex systems easier -- i.e., lead to blessing of dimensionality phenomenon -- for all the aspects of these systems: the corresponding transformation, the system's uncertainty, and the desired result of the system's analysis.
Original file
Comments
Technical Report: UTEP-CS-21-33a
Published in Entropy, 2021, Vol. 23, No. 5, Paper 501.