将非线性函数引入学习过程，由算法自动调节学习速率。
Used nonlinear function in learning, the algorithms can adjust automatically convergent rate.
最常用的评估学习速率方法是绘制预测质量-项目个数的散点图。
The most common method to evaluate the learning rate is to plot a prediction quality versus number of items.
在控制算法中提出了自调整学习速率和学习初期的分层控制方法。
In the control algorithm, methods of multiple level control during initial stage of studying with the adaptive learning rate are put forward.
结果表明，本书中的方法比直观方法的学习速率快了1000倍。
The result indicates that it is about 1000 times faster than the intuitive method.
为了改善学习速率，提出了一种确定复数神经网络初始权值的新颖方法。
To improve learning speed, a novel method for properly initializing the parameters (weights) of training complex-valued neural networks is proposed.
采用动量法和学习速率自适应法的改进BP神经网络进行风机的故障诊断。
Improved BP nerve network, adopting the momentum method and study velocity from orientation, was applied to the fault diagnosis of the fan.
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。
Here I give some references to the selection of the number of hidden-layer nodes and learning rate.
结果表明，网络的增益、学习速率和动量是影响网络收敛和稳定性的关键参数。
Restults show that the gain, learning rate and momentum are critical for network convergence and stability.
该算法在现有压缩算法的基础上改进了学习速率因子和获胜神经元算法的求法。
Based on the current algorithms, the new one had improved the learning rate factor and the winning neuron algorithm.
描述学习速率的图表，尤指在要求掌握的时间期限内，学会某种技术的进程图。
A graph that depicts rate of learning, especially a graph of progress in the mastery of a skill against the time required for such mastery.
针对本书对于钢琴学习速率提高的帮助，我在这里尝试做一下基本的数学计算。
Here is my attempt to mathematically calculate the piano learning rate of the methods of this book.
本文提出了一种改进的BP算法，该算法基于黄金分割法自适应调整网络学习速率。
This paper presents an improved BP algorithm, which can adapt learning rate using gold-segmentation.
在神经网络自学习过程中，引入了自适应学习速率和误差批处理法，加快了学习速度。
In the training process, the adaptive learning rate and error batch-mode process are introduced to accelerate the training rate.
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。
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.
神经网络的辨识采用变尺度二阶快速学习算法，利用二阶插值法来优化搜索学习速率。
In this paper, a kind of variable metric fast second order nonlinear optimization algorithm is proposed, where a second order interpolating method is used in the optimization of learning rate.
应用BP算法程序，对钢材力学性能按单隐蔽层不同结点数和不同学习速率进行预报计算。
Using BP algorithm of the neural network, the mechanical properties of rolled products have been predicted by multi joints of single hiding layer and different drilling rate.
与标准BP算法比较，该系统通过结合附加动量法和自适应学习速率形成新的BP改进算法。
Compared to the standard BP, this algorithm integrated the additional momentum method with the adaptive learning rate method.
针对BP算法收敛速度慢的特点，在隐含层上加入了关联节点，改善了网络的学习速率和适应能力。
Aiming at the slow convergence rate of BP neural network, append a correlative node on hidden layer, improve the adaptive ability and rate of studying of neural network.
对小波神经网络采用最速梯度下降法优化网络参数，并对学习率采用自适应学习速率方法自动调节。
In WNN the most fast grads descent methodology was adopted to adjust the network parameters and the learning rate by self adapting learning rate method.
我们首先简单介绍基于累积误差的梯形下降法，在此基础上，给出了一种自适应学习速率的调整方案。
First, we introduce the trapezoid drop method based on cumulative error, and give a study way of 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 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.
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。
The effects of neural network parameters including gain, learning rate, and momentum on network convergence and DPV computation results have been investigated.
为了提高网络的分类效果以及训练速度，采用了附加动量法和自适应学习速率调整法对BP算法进行了改进。
To improve the networks'classification effect and train speed, the additive momentum and self-adaptive–study-rate adjustment method are adopted further to improve traditional BP algorithm.
在神经网络自学习过程中，引入了自适应学习速率和动量法，加快了网络的收敛速度，提高了网络的辨识精度。
During the self learning process, the adaptive learning rate and momentum gene are introduced to accelerate the rate of convergence and advance the identify accuracy.
此外，通过遗传算法对模糊神经网络的学习速率和惯性系数等进行了优化，为控制系统实现最优控制提供了有力保证。
In addition, the paper makes use of Genetic Algorithms to optimize learning rates and inertia coefficients of Fuzzy-neural network, which can ensure that the controller achieves optimization control.
学习速率也属于一种非准确性功能性测量指标，能够评测推荐系统达到为新增项目或用户做推荐的合理水平所需的时间。
The learning rate also belongs to non-accuracy functional metrics and measures how quickly the rs achieves a reasonable recommendation level for recently introduced items or users.
我们可以得出这样一个结论，通过使用正确的方法，我们的学习速率可以更加接近莫扎特、贝多芬、李斯特和肖邦这些钢琴大师们。
The conclusion we should draw here is that, with the proper methods, our learning rates should be pretty close to those of the famous composers such as Mozart, Beethoven, Liszt, and Chopin.
该模型有自组织和自学习的功能，可以根据每次学习误差的不同，不断调整学习速率，加速收敛过程，充分排除数据样本的随机性影响。
The network model can organize and study itself, according to different study error, continuously adjust the study rate, and accelerate refrain process, expel influence of the data sample.
该模型学习速率快，训练步骤少，逼近程度高，最大偏差不大于5％，为三相循环流化床蒸发器的传热计算提供了可靠的方法和理论基础；
Rapid learning speed, few training steps and high fidelity are advantages of the model. The maximal deviation is no more than 5%.
该模型学习速率快，训练步骤少，逼近程度高，最大偏差不大于5％，为三相循环流化床蒸发器的传热计算提供了可靠的方法和理论基础；
Rapid learning speed, few training steps and high fidelity are advantages of the model. The maximal deviation is no more than 5%.
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