Meanwhile, combining with cognitive analysis of the process of learning Matrix and Transformation, the author puts forward teaching strategies accordingly.
同时，结合对矩阵与变换的学习过程的认知心里分析，提出相应的教学策略；
The establishment of mathematical model of PDAG algorithm, with the application of a learning matrix to the error data, proved the stability and convergence of PDAG algorithm in theory.
将学习矩阵作用于误差数据建立PDAG算法的数学模型，从理论上证明了PDAG算法的稳定性和收敛性。
Science fiction fans flocked to the site for its Snow Crash and Matrix-like neo-apocalyptic feel. And finally, educators arrived to build inexpensive and immersive learning environments.
科幻迷们蜂拥而至，后来教育者也开始在上面建立廉价的虚拟教学环境。
Up to now, some heuristic algorithms have been proposed for learning from examples based on extension matrix theory.
到目前为止，一些启发式算法被提出用于基于扩张矩阵理论的示例学习研究。
Making deep analysis of grey relational degree and devising a relational matrix, it presents a grey relational assessment model to analyze learning capability of an enterprise.
应用灰关联分析方法，设计了组织学习力影响因素关联矩阵，提出了一个分析组织学习力的灰关联评估模型。
A computational theory of learning from examples, extension matrix theory, is presented.
本文提出示例学习的一种计算理论，扩张矩阵论。
This paper presents a statistically learning fixed matrix adaptive KLT figure print image compression coding method. It is implemented using TMS320C25 as well.
本文提出一种统计训练固定矩阵自适应KLT指纹图像压缩编码方法，并在TMS320C 25信号处理器上实时实现。
Then, the learning of the weight matrix can be done by means of solving a group of systems of linear equations. Last, the mathematical base of the outer-product leaming method is pointed out.
将权矩阵的学习过程归结为用梯度下降法求一组矛盾线性方程组的过程；
Based on bilingual corpora, the algorithm can produce words-similarity-matrix through machine learning.
该算法能基于双语语料，通过机器学习来自动进行语义聚类，生成词间相似度矩阵。
The basic idea of this learning rule is to obtain a certain optimization by continuously changing the elements of coupling matrix selected randomly.
这种学习规则的基本思想就是：通过不断地优化变异随机选择的连接权矩阵元，从而使网络在给定的训练目标下达到整体最优。
Based on the model, the Taylor series coefficients of control function are adjusted by an iterative learning law and the learning gain matrix is designed via LMI optimization.
模型的基础上，泰勒级数的系数调整控制功能的迭代学习法律，学习增益矩阵，通过LMI优化设计。
And based on the experimental results of multi-dimensional data clustering, anomaly detection matrix is determined through identifying the training sample set and the machine self-learning.
然后根据对多维数据聚类的实验分析结果，通过对样本集的训练进行标识和机器自学习过程来判别异常检测矩阵。
And based on the experimental results of multi-dimensional data clustering, anomaly detection matrix is determined through identifying the training sample set and the machine self-learning.
然后根据对多维数据聚类的实验分析结果，通过对样本集的训练进行标识和机器自学习过程来判别异常检测矩阵。
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