计算机工程2009，Vol.35Issue(22)：200-201,204,3.
基于RBF神经网络与RLS算法的均衡器
Equalizer Based on RBF Neural Network and RLS Algorithm
摘要
Abstract
This paper combines Radial Base Function(RBF) neural network and landscape filter, uses Recursive Least Square(RLS) algorithm to update the weight and uses variable steps associated with errors, the output error and the convergence speed are both improved. Simulations results show that the new equalizer has better performance, whether it is in linear or nonlinear. In more serious cases, its advantages are much more obvious.关键词
径向基函数神经网络/递推最小二乘算法/代价函数Key words
Radial Base Function(RBF) neural network/Recursive Least Square(RLS) algorithm/cost function分类
信息技术与安全科学引用本文复制引用
吕志胜,赖惠成..基于RBF神经网络与RLS算法的均衡器[J].计算机工程,2009,35(22):200-201,204,3.基金项目
新疆维吾尔自治区高校科学研究计划基金资助项目(XJEDU2006I10) （XJEDU2006I10）
