Impacts of Perturbations of Training Patterns on Two Fuzzy Associative Memories Based on T-Norms.

In general, there is perturbation between collected training pattern and its corresponding actual pattern in real world, such perturbation may cause disadvantage to performance of a fuzzy neural network, therefore a type of robustness of fuzzy associative memories (FAMs) is proposed correlative with the perturbations of training patterns in the paper, then it is pointed out that using the maximum-weight-matrix learning algorithm, a Max-T0 FAM has poor such robustness, however, a Max-TL FAM holds good robustness, where the two FAMs are based on t-norm T0 and Lukasiewicz t-norm, respectively. Finally, a simulation experiment validates our theoretical results. [ABSTRACT FROM AUTHOR]