归一化LMS盲最大似然序列估计算法

The Normalized Blind LMS MLSE Algorithm

阐述了归一化LMS盲最大似然估计算法的基本原理,通过计算机仿真试验证明了该算法在收敛速度、稳态剩余误差等方面均优于传统的LMS盲最大似然估计算法,并提出了该算法的研究方向。

This paper expounds the basic principle of the normalized blind LMS MLSE （ maximum likelihood sequence estimation） algorithm, and by using the computer simulation experiment, proves that this algorithm is better than the traditional blind LMS MLSE algorithm in the convergence speed and the mean square error, and advances the developing direction of this algorithm.