实时半盲非线性均衡算法:N-伪递推模糊C-均值均衡算法

A New Real-Time Quasi-Blind Nonlinear Equalization Algorithm:N Pseudo Recursive Fuzzy C-means Algorithm(N-PRFCM)

本文基于模糊C-均值算法设计了能对不在同一时刻到达的数据进行实时模糊聚类的N-伪递推模糊c-均值算法(N Pseudo Recursive Fuzzy c-means A lgorithm,简记为N-PRFCM),并将其应用到非线性均衡上(N-PRFCM均衡算法).仿真结果表明,该算法具有实时、半盲、聚类中心的自适应变动的特性,且由于该算法关心的仅是信道聚类中心间的距离,故信道非线性畸变程度对它的影响可忽略不计.最后对该算法进行了收敛性分析.

N pseudo recursive fuzzy c-means algorithm （N-PRFCM） is designed. It can cluster data which can＇t reach at the same time lively. It is used in nonlinear equalization. Experimental results show the algorithm is real -time, quasi-blind and having adaptive cluster centers. At last, we analyze its convergence.