Title :
The designing and training of a fuzzy neural Hamming classifier
Author :
Hua, Qiang ; Zhen, Qi-lun
Author_Institution :
Huizhou Univ., China
Abstract :
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
Keywords :
Hamming codes; fuzzy neural nets; pattern recognition; VLSI technology; comparison subnet; fuzzy class membership; fuzzy neural Hamming classifier; integer threshold; pattern overlap; Artificial neural networks; Convergence; Emulation; Integrated circuit interconnections; Neural networks; Neurons; Pattern matching; Pattern recognition; Very large scale integration;
Conference_Titel :
Multiple-Valued Logic, 2001. Proceedings. 31st IEEE International Symposium on
Conference_Location :
Warsaw
Print_ISBN :
0-7695-1083-3
DOI :
10.1109/ISMVL.2001.924595
