基于增强型模糊神经网络的盲均衡算法研究

A New Blind Equalization Algorithm Based on the Enforced Fuzzy Neural Network

提出一种利用增强型模糊神经网络进行盲均衡的新算法.增强型模糊神经网络具有很好的非线性逼近能力和映射能力,符合非线性通信技术处理的特点.给出增强型神经网络的结构和状态方程,提出代价函数,推导出均衡参数的迭代公式.仿真表明,本算法收敛后误码率减减小,收敛效果较好.

A new blind equalization algorithm based on the Enforced Fuzzy Neural Net- work（EFNN）is proposed in this paper. The EFNN has higher accuracy of closing nonlinear system and better mapping capability, so it accords with the characteristic of nonlinear com- munication technology processing. In this paper, the structure and the state functions of the EFNN are given, the cost function is proposed, and the parameter iteration formula are derived. Computer simulation results show that the new algorithm has better convergence effect, lower bit error rate than the forward NN algorithm.