On new fuzzy morphological associative memories
In this paper, the new fuzzy morphological associative memories (FMAMs) based on fuzzy operations (Lambda, .) and (V, .) are presented. FMAM with (V, .) is extremely robust for dilative noise and FMAM with (Lambda, .) is extremely robust for erosive noise. Autoassociative FMAM has the unlimited storage capability and can converge in one step. The convex autoassociative FMAM can be used to achieve a reasonable tradeoff for the mixed noise. Finally, comparisons between autoassociative FMAM and the famous FAM are discussed. FMAM, as another new encoding way of fuzzy rules, still has a multitude of open problems worthy to explore in the future.
associative memories fuzzy operations storage capability convergence fuzzy rules