培生则将获得Knewton自适应学习技术的部分专有权。
Pearson will get semi-exclusive access to Knewton's adaptive learning technology.
提出一种基于区域自适应学习的人脸图像超分辨率复原算法。
A novel region adaptive learning-based super resolution algorithm for human face images is proposed, which divides a face image into flat regions and detailed regions.
使用自适应学习率的算法调整网络的权值，加快了网络的学习速度。
Using an algorithms of adaptive learning rates adjust the network's weight for quickening learning rates.
该方法实时性好、可靠性高，而且具备自适应学习能力，有一定的应用价值。
The method has many advantages such as good performance of on-line, high reliability, ability for self-adapting and study on-line, and is of particular value in application.
介绍遗传算法的基本原理，并采用自适应学习遗传算法排定某露天边坡的开挖步序。
The fundamental of genetic algorithms is introduced. Excavation schedule of slope is determined by means of adaptive learning genetic algorithms.
该方法采用增量学习的思想，对话题追踪任务中的自适应学习机制提出了新的算法。
This method adopts the idea of increment learning, and presents new algorithm to the adaptive learning mechanism in the task of topic tracking.
该方法采用增量学习的思想，对话题追踪任务中的自适应学习机制提出了新的算法。
Based on the idea of increment learning, the paper presents a new algorithm for the adaptive learning mechanism in the task of topic tracking.
阐述了混沌学习算法的机理，设计了交通流量WNN混沌时间序列自适应学习算法。
Then the mechanism of the chaotic learning algorithm is described, and the adaptive learning algorithm of WNN for traffic flow time series is designed.
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.
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。
At last, a kind of BP algorithm with adaptive learning rate is evaluated and compared with standard BP algorithm by XOR problem.
提出了一种隐层结构自适应学习的径向基函数网络(HSARBF)水声目标分类器。
This paper proposes a hidden layer structure adaptive radial basis function (HSARBF) classifier.
特别是对阈值去噪方法，提出了一种基于正交小波变换和自适应学习算法的噪声抑制方法。
Especially to threshold de-noising, a method based on orthogonal wavelet analysis and self-adaptive learning algorithm was proposed here.
此刻，我们乂学教育与哥伦比亚大学教育学院的自适应学习研究联合实验室正式成立了！
We are officially opening the Classba Research Lab on Adaptive Learning at Teachers College, Columbia University.
文中提出一种基于模糊自适应学习控制(FALCON)结构下新型的混合学习控制策略。
A new fuzzy adaptive learning control (FALCON), structure based mixture learning control is put forward in the paper.
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.
BP神经网络具有很强的非线性映射和自适应学习功能，可用于模式识别和预测评估等领域。
The BP neural network has ability of nonlinear-mapping and self-accommodating. It can be used to recognize mode, forecast and so on.
提出将IRT的相关算法应用于在线教学系统，通过相应的算法，实现自适应学习管理和跟踪。
The paper proposes an online teaching system based on IRT, and by this system, the managing and tracing process of adaptive learning are realized.
该算法克服单准则的局限性，更好地模拟人脑的自适应学习功能，可以实现更有效的学习和识别。
This arithmetic overcome the demerit of single rule, and is better to simulate the studying function of the brain.
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.
仿真及试验结果表明，该网络具有良好的表达能力和极强的自适应学习能力，能正确识别较复杂的轨迹。
Emulation and experiments show that NFNN has fine expression and auto adapt learning and identifying complex track ability.
非常荣幸能在此和诸位共同见证自适应学习领域、教育研究领域、以及全球教育科技行业这一历史性的时刻。
It is my great honor to be here with you, to witness a historic moment in the field of adaptive learning, in educational research, and in the global EdTech industry.
提出了一种基于神经元状态融合的组合导航系统信息融合模型，给出了神经元融合权重在线自适应学习算法。
An information fusion model of integrated navigation system based on neurons is proposed, and also an on line adaptive training algorithm of the weights of neuron is given.
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。
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.
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.
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.
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