The designing and training of a fuzzy neural Hamming classifier
Qiang Hua, Qi-lun Zhen · 2002
The Fuzzy Neural Hamming Classifier (FNHC) can resolve the pattern overlap with the degree of fuzzy class membership; ensure the convergence and decrease the interconnection with the comparison subnet; accept both binary and non-binary input. Using only integer threshold and weights, FNHC is easily implemented in VLSI technology.