Some Theoretical Aspects of max-C and min-D Projection Fuzzy Autoassociative Memories

Abstract

Autoassociative memories (AMs) are models inspired by the human ability to store and retrieve information by association. A fuzzy associative memory is used for the storage and recall of fuzzy sets. Inspired by the fuzzy morphological associative memories, we recently introduced the class of max-C projection fuzzy autoassociative memories (maxC PFAMs). In few words, a max-C PFAM projects the input vector into the set of all max-C combinations of the stored vectors. In this paper, we present its dual version, the class of min-D PFAMs, which projects an input into the set of all min-D combinations. In this paper we also address some theoretical issues of the two PFAM models.