Title :
On new fuzzy morphological associative memories
Author :
Wang, S.T. ; Lu, H.J.
Author_Institution :
Dept. of Comput. Sci. & Technol., Southern Yangtze Univ., Jiangsu, China
fDate :
6/1/2004 12:00:00 AM
Abstract :
In this paper, the new fuzzy morphological associative memories (FMAMs) based on fuzzy operations (∧,·) and (∨,·) are presented. FMAM with (∨,·) is extremely robust for dilative noise and FMAM with (∧,·) 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.
Keywords :
content-addressable storage; fuzzy logic; fuzzy neural nets; memory architecture; random noise; dilative noise; fuzzy morphological associative memories; fuzzy operations; fuzzy rules; mixed noise; storage capability; Associative memory; Computer science; Convergence; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Image coding; Neural networks; Noise robustness; Subspace constraints; Associative memories; convergence; fuzzy operations; fuzzy rules; storage capability;
Journal_Title :
Fuzzy Systems, IEEE Transactions on
DOI :
10.1109/TFUZZ.2004.825977
