Blind Equalization Algorithm Based on Fuzzy Neural Network in QAM System

摘要：

A new blind equalization algorithm based on fuzzy neural network classifier was proposed. It was applied in the QAM System. Channel estimation and fuzzy neural network classifier are combined to carry out blind equalization. The primary signal was attained by de-convolution. Judgment range of fuzzy neural network was adjusted dynamically by competition study algorithm, and then blind equalization was realized. Simulations illuminate that the new algorithm improves convergence speed and reduces residual error and BER (Bit Error Ratio).

作者: SHEN Fang SUN Yunshan ZHANG Liyi LI Yanqin LI He

作者单位: Tianjin University of Commerce, China Taiyuan University of Technology, China

会议类型: 国际会议

会议名称: 2nd IEEE Conference on Industrial Electronics and Applications(ICIEA 2007)(第二届IEEE工业电子与应用国际会议)

会议地点: 哈尔滨

会议语种:英文

在线出版日期: 2007-05-23（万方平台首次上网日期，不代表论文的发表时间）