【摘要】 本文给出了多维小波网络的结构及其随机梯度学习算法 ,提出了基于小波网络的MQAM数字通信自适应均衡器 .仿真结果表明 :该均衡器对于MQAM数字信号非线性信道的均衡 ,其性能明显优于传统的基于LMS和RLS算法的线性均衡器和基于RLS算法的判决反馈均衡器 ,且性能稍好于基于BP网络的均衡器 ,其缺点是计算复杂度高和训练收敛速度慢更多还原

【Abstract】 A novel wavelet network based adaptive equalizer (WNBAE) is presented and the structure and stochastic gradient learning algorithm is given. The proposed WNBAE has better performance than that of the conventional linear transversal equalizer based on the LMS and the RLS algorithms, as well as that of the decision feedback equalizer based on the RLS algorithm, especially for MQAM digital communication reception systems over the nonlinear channels. In addition, it outperforms the BP neural network based adaptive equalizer slightly. However, it has a slow convergence rate and a high computational complexity. Several simulations are performed to evaluate the behavior of the WNBAE.更多还原