University of Al-Qadisiyah Al-Qadisiyah Journal for Engineering Sciences 1998-4456 7 2 2014 06 28 UTILIZING FUZZY RECOGNITION IN HOPFIELD NEURAL NETWORK IN RELATIVELY HIGH CORRUPTION SIGNAL TRANSMISSION استخدام المنطق الضبابي في تحديد الأشكال التي لا يتم فيها التطابق عند تقارب شبكة الخلايا العصبية نوع ذاكرة الاقتران " هوبفيلد" في ظل تشوه عالي بالإشارة المرسلة نسبي 225 238 90784 EN Ismael Khaleel Murad Journal Article 2014 06 01 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. Fuzzy Logic linear associative Memory Recurrent Neural Network Hopfield Network Corruption Bipolar Transmission https://qjes.qu.edu.iq/article_90784_e167865a68a7d42a03bffd1e733674e6.pdf