本文利用基于最小均方算法（Least Mean Square algorithm，LMS）的复径向基函数神经网络均衡器（Complex Radial Basis Function Netwo...
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recursive least mean square algorithm 递推最小二乘算法
normalized least mean square algorithm 归一化最小均方算法
trans-propagation least mean square algorithm 横向传播最小均方算法
least mean square error algorithm 最小均方误差算法
least mean square adaptive algorithm 最小均方自适应算法
least mean square iterative algorithm 最小均方迭代算法
least mean square self-adaptive algorithm 最小二乘均方自适应算法
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After coarse frequency synchronization, frequency offset compensation is carried out using variable step size least mean square algorithm (VLMS).
经过频率粗同步后，以变步长的最小均方算法(VLMS)进行频率补偿。
The connection weights between hidden layer and output layer are got by Least Mean Square Algorithm.
径向基函数神经网络的隐含层到输出层的线性连接权值，则是由最小二乘法来计算得到的。
It is shown in this paper that the Least-Mean-Square algorithm cannot minimize the mean square error, and that it is actually a kind of weighted Least-Square algorithm.
本文指出最小均方算法并不能使均方误差最小，证明了最小均方算法实际上是一种加权最小二乘算法。
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