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A blind equalization algorithm based on fuzzy neural network was proposed. Blind channel estimation and fuzzy neural network classifier were utilized to realize blind equalization. Firstly Blind channel estimation was used to identify the character of the channel. Signals were rebuilt by de-convolution, and the original judgment equipment was replaced by fuzzy neural network classifier. Simulations...
As a key technology of digital broadcast and TV, blind equalization overcomes inter-symbol interference to improve the effect of receiving signals. A new QAM blind equalization algorithm based on fuzzy neural network classifier was proposed. Simulation shows that the new algorithm improves convergence speed and reduces residual error and BER (bit error ratio).
As a key technology in the digital communication system, blind equalization algorithm based on fuzzy neural network classifier is proposed. The algorithm overcomes bad judgment error. Channel estimation algorithm and fuzzy neural network classifier were combined to carry out equalization. The primary signal was attained by de-convolution. Judgment range of fuzzy neural network was adjusted dynamically...
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