How to Speed Up Computations

  • Andrew PownukEmail author
  • Vladik Kreinovich
Part of the Studies in Computational Intelligence book series (SCI, volume 773)


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.

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Computational Science ProgramUniversity of Texas at El PasoEl PasoUSA

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