Type-2 Fuzzy Alpha-Cuts

Type-2 fuzzy logic systems make use of type-2 fuzzy sets (T2FS). To be able to deliver useful type-2 fuzzy logic applications we need to be able to perform meaningful operations on these sets. These operations should also be practically tractable. However, T2FS suffer the shortcoming of being complex by definition. Indeed, the third dimension, which is the source of extra parameters, is in itself the origin of extra computational cost. The quest for a representation that allow practical systems to be implemented is the motivation for our work. In this paper, we define the alpha-cut decomposition theorem for T2FS which is a new representation analogous to the alpha-cut representation of type-1 fuzzy sets and the extension principle. We show that this new decomposition theorem forms a methodology for extending mathematical concepts from crisp sets to T2FS directly. In the process of developing this theory, we also define a generalization that allows us to extend operations from interval T2FS or interval valued fuzzy sets to T2FS. These results will allow for the more applications of T2FS by expiating the parallelism that the research here affords.