In this paper, a new Evolution Strategy method for solving matrix eigenvalues and eigenvectors was proposed.
提出了一种基于进化策略求解矩阵特征值及特征向量方法。
In this paper, a kind of inverse eigenvalue problem which is the reconstruction of real symmetric five-diagonal matrix by five eigenvalues and corresponding eigenvectors is proposed.
本文讨论了一类由五个特征值和相应特征向量构造实对称五对角矩阵的特征值反问题。
Taking image as a matrix, an eigenface algorithm USES eigenvalues and corresponding eigenvectors in recognition.
本征脸法将图像看做矩阵，计算本征值和对应的本征向量作为代数特征进行识别。
Then, an image scatter matrix is constructed using the reshaped image matrixes and its eigenvectors are derived for image feature extraction.
该方法先将图像矩阵进行重组，根据重组的图像矩阵构造出总体散布矩阵，然后求出最佳投影向量进行特征提取。
This paper presents a neural network approach to computing the eigenvectors corresponding to tae largest and smallest eigenvalues of a positive matrix.
本文给出实时求解正定矩阵最小和最大特征值对应特征矢量的神经网络模型。
This paper provides an efficient algorithm for finding all the eigenvalues and partial eigenvectors of a real matrix.
本文提供求实矩阵全部特征值及部分特征矢量的一个富有成效的算法。
In this paper, the defects of modular 2dpca about computing the total scatter matrix of training samples and selecting eigenvectors are analyzed. An improved modular 2dpca algorithm is presented.
本文分析了模块2dpca在计算训练样本总体散布矩阵和本征向量选取方面的缺陷，提出了一种改进的模块2dpca算法。
In this paper, the defects of modular 2dpca about computing the total scatter matrix of training samples and selecting eigenvectors are analyzed. An improved modular 2dpca algorithm is presented.
本文分析了模块2dpca在计算训练样本总体散布矩阵和本征向量选取方面的缺陷，提出了一种改进的模块2dpca算法。
应用推荐