The multiplier on the global learning rate for this parameter.

这是一个通用的参数。

The learning process use the constant learning rate in the traditional reinforce learning model, because of that robot learn in a low convergence speed and with the poor adaptation.

传统的强化学习模型在整个学习过程中使用恒定学习速率，导致在未知环境下收敛速度慢且适应性差。

The learning rate is an important parameter for the learning process of a neural network(NN)which influents the stability and quickness of the NN.

学习速率是控制神经网络学习过程的一个重要参数，影响神经网络的稳定性和快速性。

Here I give some references to the selection of the number of hidden-layer nodes and learning rate.

在这里我们对于隐含层节点数选择、学习速率选择等问题提出一些参考意见。

X(p,i,n) is the ith element in p that is input into node n, and alpha is the already noted learning rate.

X(p,i,n)是输入到节点n 的p中的第i 个元素，alpha是已知的学习率。

At last, a kind of BP algorithm with adaptive learning rate is evaluated and compared with standard BP algorithm by XOR problem.

最后结合XOR问题把一种自适应学习率BP算法和标准BP算法进行了比较和评价。

The effects of neural network parameters including gain, learning rate, and momentum on network convergence and DPV computation results have been investigated.

详细地讨论了增益、学习速率、动量等网络参数对神经网络收敛速度和导数脉冲伏安法计算结果的影响。

In the paper, a modified constant modulus algorithm (MCMA) is proposed. The proposed algorithm minimizes a modified error function and the learning-rate is multiplied by received sequences.

采用一种修正恒模算法（MCMA），该算法使修正的误差函数最小并且自适应学习率由接收序列即时调整。