Abstract
In this paper, a dynamic fuzzy neural network (DFNN) is applying for communication channel equalization problem. By combining fuzzy rules with the learning ability of neural networks, DFNN can achieve the advantages of both fuzzy logic and neural networks. The simulation results show that DFNN equalizer is superior to other equalizers such as recurrent neural network (RNN) and minimal resource allocation networks (MRAN) in terms of bit error rate (BER).
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