多层感知器信道均衡器

Multilayer perception equalizer

利用多层感知器自学习、非线性映射能力,提出一种自适应多层感知器信道均衡的模型,这种模型不仅对信道线性失真,而且对非线性失真也有很好的补偿作用。分析了人工神经网络(ANN)均衡器的设计方法,由于精确地分析感知器均衡器的位误差概率很困难,故通过模拟仿真的方式结出了与线性均衡器的性能比较。

This paper developed a multilayer perception adaptive equalizer model which uses the self-learning and nonlinear capability of Neural net(NN). This model has the ability to compensate not only for the linear distortion but also for the nonlinear distortion. Since exact analysis of the bit error probability for neutral net equalizer is very difficu, we consider simulation to compare its performance with the linear equalizer.