On the Generation of Hyper-powersets for the DSmT

Mathematics – General Mathematics

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

11 pages, 2 tables, one graph, one computer program. Presented to The Sixth International Conference on Information Fusion, Ca

Scientific paper

The recent theory of plausible and paradoxical reasoning (DSmT for short, or Dezert-Smarandache Theory), developed by the authors, appears to be a nice promising theoretical tools to solve many information fusion problems (for example in military defense, medicine, etc.), where the Shafer's model cannot be used due to the intrinsic paradoxical nature of the elements of the frame of discernment and where a strong internal conflict between sources arises. The main idea of DSmT is to work on the hyper-powerset of the frame of discernment of the problem under consideration. Although the definition of hyper-powerset is well established, the major difficulty in practice is to generate such hyper-powersets in order to implement DSmT fusion rule on computers. We present in this paper a simple algorithm for generating hyper-powersets and discuss the limitations of our actual computers to generate such hyper-powersets when the dimension of the problem increases.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

On the Generation of Hyper-powersets for the DSmT does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with On the Generation of Hyper-powersets for the DSmT, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and On the Generation of Hyper-powersets for the DSmT will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-651203

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.