The LMS algorithm is usually adopted to adjust weight coefficients of the adaptive transversal filter whose output is an estimation of the echo signal.
通常采用LMS算法对自适应横向滤波器的加权系数进行调节。
This paper discusses the relationship among the correlation of input signal, weights number and steady state square error of the LMS algorithm in detail.
该文详细讨论了LMS算法中输入信号相关性、加权数目和稳态均方误差的关系。
In the cases where the fast convergence and tracking behaviors are required, the LMS algorithm and the conventional fast Kalman algorithm are not suitable.
在要求快速收敛和跟踪的场合下，lms算法及常规的快速卡尔曼算法均不适用。
The presented algorithm is easy to be implemented and the difference between the accurate value and the result obtained by using the LMS algorithm is acceptable in practical application.
结果证明，采用LMS算法得出的结果与准确值的偏差在工程上完全可以接受，并且算法容易实现。
The correlation algorithm in training period and the LMS algorithm in run period can be combined in the identical transversal filter structure, so that it speeds up the channel estimator convergence.
训练阶段的相关算法与工作阶段的LMS算法可结合在同一个横向滤波器结构中，从而加速了自适应信道估计器的收敛过程。
The correlation algorithm in training period and the LMS algorithm in run period can be combined in the identical transversal filter structure, so that it speeds up the channel estimator convergence.
训练阶段的相关算法与工作阶段的LMS算法可结合在同一个横向滤波器结构中，从而加速了自适应信道估计器的收敛过程。
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