有向无环图支持向量(DAG-SVMS)多类分类方法，是一种新的多类分类方法。
Directed acyclic graph support vector (DAG - SVMS) multi - category classification methods, is a new multi - category classification methods.
在字符识别部分，提出了在无特征提取情况下基于支持向量机的车牌字符识别方法。
A local projection method is used to segment character. At Last, a License Plate Recognition method based support vector machines is proposed.
分析在有或无左室梗死条件下急性右室梗死心向量图改变。
Analyze VCG changes of ARVI with and without the condition of inferior, posterior infarction of left ventricle.
此外，采用一种动态位向量(DBV)的压缩机制对无向图中边的权重进行压缩存储，以有效地提高算法的空间存储效率。
Besides, the compression mechanism of Dynamic Bit Vector (DBV) was used to store the edge weights in undirected graph to improve the spatial storage efficiency of the algorithm.
支持向量机（SVM）反问题研究的是如何把无类标签的数据集合分成两类才能得到最大的间隔。
The inverse problem of Support Vector Machine (SVM) is how to split the dataset into two clusters so that the margin between the two clusters reaches maximum.
在无噪声的情况下，使用任意一阶模态数据，残余力向量法都能够对损伤进行准确定位。
The first step identifies the location of the possible damaged poles by analyzing the joint residual force vector.
在无噪声的情况下，使用任意一阶模态数据，残余力向量法都能够对损伤进行准确定位。
The first step identifies the location of the possible damaged poles by analyzing the joint residual force vector.
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