How to Speed Up Computations
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In this chapter, we describe cases for which we can speed up computations. We start, in Sect. 3.1, with the case of fuzzy uncertainty under min t-norm, for which, as we mentioned in Chap. 1, data processing means using Zadeh’s extension principle, or, equivalently, interval computations on \(\alpha \)-cuts. In this case, processing different types of uncertainty separately can drastically speed up computations. For the important case of t-norms different from min, a similar speedup is described in Sect. 3.2. In Sect. 3.3, we describe a speedup for the case of probabilistic uncertainty. Finally, in Sect. 3.4, we speculate on the possibility of use quantum computing to further speed up data processing.