摘要
针对严重非线性失真信道,提出了一种级联混合小波神经网络自适应盲均衡器.这种均衡器在小波网络输入层之前级联一个横向滤波器,横向滤波器的节点输出作为小波网络的输入.利用常数模代价函数分别获得横向滤波器和小波网络的梯度信息,将两个梯度信息进行加权融合处理,可以得到混合小波网络参数调整的梯度信息.级联混合小波网络盲均衡器实现了对非凸性误差性能曲面的线性和非线性寻优的组合.普通电话信道和非线性信道条件下的仿真结果表明,级联混合小波网络盲均衡与前馈网络盲均衡以及传统小波网络盲均衡相比较,具有更好的均衡性能.
A cascaded hybrid wavelet neural network （WNN） adaptive blind equalizer is proposed for severe nonlinear distortion channel. This equalizer cascades a transversal filter before the input layer of WNN, and the input signal of WNN is inferred from the output of the nodes of the transversal filter. The gradient information of the transversal filter and WNN can be obtained by constant modulus cost function respectively, and then the gradient information for updating the parameters of the hybrid WNN can be obtained by weighted fusion of the two gradient information. The cascaded hybrid WNN blind equalizer realizes the combination of linear and nonline^u~ optimization on non-convexity error surface. Simulation results with ordinary telephone channel and nonlinear channel show that the cascaded hybrid WNN blind equalizer has a better equalization performance comparing with FNN （feedforward neural network） and traditional WNN blind equalizers.
出处
《信息与控制》
CSCD
北大核心
2009年第4期479-483,共5页
Information and Control
关键词
小波神经网络
盲均衡
代价函数
加权融合
wavelet neural network
blind equalization
cost function
weighted fusion
