正定二次型

  • 网络Positive definite quadratic form;positively definite quadratic form
正定二次型正定二次型
  1. 拉格朗日乘数法给出了多元函数条件极值的必要条件,本文利用正定二次型理论证明多元函数条件极值的一个充分条件。

    Lagrange multiplier method provides necessary conditions for the constrained extreme value of the function of many variables , so this paper , based on the theory of positive definite quadratic form , proves the sufficient condition for the constrained extreme value of the function of many variables .

  2. 地震波的场方程矩阵和能量的正定二次型及其意义

    The significance of seismic wave field equations matrices and the energy positive definite quadratic form

  3. 线性泛函在正定二次型下的范数

    Norm of a Linear Functional for a Positive Definite Quadratic Form

  4. 半正定二次型的性质及应用

    The Character an the Application for Semi-definite Positive Quadratic Form

  5. 半正定二次型及半正定矩阵

    Positive Semidefinite Quadratic Form and Positive Semidefinite Matrix

  6. 借助矩阵的合同变换法,给出了化实二次型为标准形的方法、求标准正交基的方法,并给出了正定二次型判定定理的新证明。

    By means of congruent transformation in matrix , the method of transforming real quadratic form into standard form and the method of normal orthogonal basis are given in this paper .

  7. 最后,运用矩阵的正定二次型理论阐述了能量矩阵与弹性矩阵之间一致的对称性和正定性。

    At last the consistently symmetrical and positive definite properties between the energy matrices and the elastic matrices are clarified by using the theory of positive definite quadratic form of matrices .

  8. 当控制域为凸多面体,泛函指标为正定二次型时,给出该社区居民医疗保健费用的预测估计与最佳控制表达式。

    When the controlling area is convex polytope , and the functional indicatrix is positive definite quadratic form , out come the estimation and optimum control expression on health care costs of residents in the community .

  9. 对部分变元正定的二次型函数的构造

    On the structure of the partial positive definite quadratic forms

  10. 关于在扇形域内正定的二次型

    On positive definite quadratic form in a region of sector

  11. 若A是对称正定矩阵,则二次型x~TAx能写成平方项的和,即A是秩为1的矩阵VV~T的和。

    If A is a symmetric positive definite matrix , then the quadratic form x ~ TAx can be written as a sum of squares . Equivalently , A is a sum of rank one matrices VV ~ T.