eigenvalue and eigenvector 中文意思是什麼

eigenvalue and eigenvector 解釋
本徵值和本徵向量
  1. Firstly, it introduced the import principium resolving thread and steps of analytic hierarchy process. secondly, it erected model of population modernization, which based on the steps of analytic hierarchy process. lastly, it got the maximal eigenvalue of dissymmetric matrix and corresponding eigenvector with sas, and normalized the eigenvector to get weight value

    本章分為兩部分，第一部介紹分析法的提出、原理以及解決問題的思路和步驟；第二部建立模型確定權重，根據層次分析法的原理和步驟，建立人口現代化指標體系的模型，運用sas求解所構造的非對稱判斷矩陣的最大特徵值，從而得出所對應的特徵向量，變形后得到權重。
  2. A simple method for solving matrix eigenvalue and eigenvector

    求矩陣的特徵值與特徵向量的一種簡捷方法
  3. Exact solution of eigenvalue and eigenvector derivatives and its application in structural dynamics

    結構動力學中具有重特徵值的靈敏度分析
  4. In addition, the backward error for eigenvalue and eigenvector are analyzed respectively

    此外還單獨考慮了對特徵值和對特徵向量的結構向後誤差和向後誤差。
  5. Initial vector and iterating control in the solution to eigenvalue and eigenvector of a matrix by the matrix iterarion method

    乘冪法求矩陣特徵向量與特徵值的初始向量及循環控制
  6. Improve the traditional method of solving algebraic eigenvalue and eigenvector, give a new method of solving algebraic eigenvalue and eigenvector with elementary transformation

    摘要改進了求代數特徵值與特徵向量的傳統方法，給出了一種用初等變換來求代數特徵值與特徵向量的方法。
  7. In this paper, through treating lines reciprocal transformation to a matrix, cogradiently reach the eigenvalue and eigenvector of a matrix, to solve the question treat a eigenvalue under without parameters, and given some advanced theorems

    摘要通過對矩陣進行行列互逆變換，同步求出矩陣特徵值及特徵向量，解決了不帶參數求特徵值問題，並給出一些新定理。
  8. We prove that 0 is the eigenvalue of the system ' s host operator, and finally we give the eigenvector of the eigenvalue 0

    並證明了0是系統主運算元的本徵值，給出了0本徵值對應的本徵向量。
  9. The characteristic value of the so - called inverse algebraic eigenvalue problem is that under certain restrict conditions against the question, elements of matrix are determined according to eigenvalue or eigenvector. the practical inverse alebraic eigenvalue problem arose in phisical chemistry in the study of molecular structures. it arises in various areas of application in a lot of filelds, such as dispersed system of physical mathematic, design of vibration system of the structure, correct and control, particle nuclear spectroscopy, linear variable control system and so on

    所謂代數特徵值反問題就是在一定的限制條件下，根據給定的特徵值或特徵向量決定矩陣的元素，它是在研究物理化學中研究分子結構時發現的。矩陣特徵值反問題在數學物理反問題的離散系統、結構振動系統的設計、校正與控制、粒子物理的核光譜學、線性多變量控制系統的極點配置等許多領域都具有重要的應用。
  10. One - dimension noise subspace - based method always assumes that only the minimum eigenvalue of the signal covariance matrix is the noise eigenvalue, and the corresponding eigenvector is the true noise vector and constructs the one - dimension noise subspace

    基於一維噪聲子空間方法始終認定只有信號協方差矩陣的最小特徵值才是噪聲特徵值，其對應的特徵向量才是真正的噪聲向量，並構成一維噪聲子空間。
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