ABSTRACT
This paper studies the utilization of fuzzy logic on pattern recognition sender after analyzing unknown pattern converged from associative. In order to specify the original patterns stored in memory. Results indicated that the addition of fuzzy stage to Hopfielf net to identify the unknown pattern called (FRS) was succeeded in differentiating and identifying unknown patterns were produced by “Hopfield neural network associative memory “(HNMAR) despite of the increasing in signal corruption to relatively high levels. It was demonstrated the possibility of rising the level of performance of memory type “Hopfield” where the signal corruption is at relatively higher percentage.
Khaleel Murad,I . (2014). UTILIZING FUZZY RECOGNITION IN HOPFIELD NEURAL NETWORK IN RELATIVELY HIGH CORRUPTION SIGNAL TRANSMISSION. Al-Qadisiyah Journal for Engineering Sciences, 7(2), 225-238.
MLA
Khaleel Murad,I . "UTILIZING FUZZY RECOGNITION IN HOPFIELD NEURAL NETWORK IN RELATIVELY HIGH CORRUPTION SIGNAL TRANSMISSION", Al-Qadisiyah Journal for Engineering Sciences, 7, 2, 2014, 225-238.
HARVARD
Khaleel Murad I. (2014). 'UTILIZING FUZZY RECOGNITION IN HOPFIELD NEURAL NETWORK IN RELATIVELY HIGH CORRUPTION SIGNAL TRANSMISSION', Al-Qadisiyah Journal for Engineering Sciences, 7(2), pp. 225-238.
CHICAGO
I Khaleel Murad, "UTILIZING FUZZY RECOGNITION IN HOPFIELD NEURAL NETWORK IN RELATIVELY HIGH CORRUPTION SIGNAL TRANSMISSION," Al-Qadisiyah Journal for Engineering Sciences, 7 2 (2014): 225-238,
VANCOUVER
Khaleel Murad I. UTILIZING FUZZY RECOGNITION IN HOPFIELD NEURAL NETWORK IN RELATIVELY HIGH CORRUPTION SIGNAL TRANSMISSION. QJES. 2014;7(2):225-238.
