diagonalization argument
对角线论证
method of diagonalization
对角线化方法
diagonalization technique
对角线化技术
diagonalization proof
对角线化证明
diagonalization process
对角线化过程
diagonalization strategy
对角线化策略
performing diagonalization
执行对角线化
diagonalization algorithm
对角线化算法
diagonalization theorem
对角线化定理
matrix diagonalizations simplify the computation of matrix powers.
矩阵对角化简化了矩阵幂的计算。
simultaneous diagonalizations are possible if two matrices commute.
如果两个矩阵可以交换，那么可以同时对角化。
the proofs rely heavily on various abstract diagonalizations.
这些证明大量依赖于各种抽象的对角化。
we must perform numerical diagonalizations to find the eigenvalues.
我们必须进行数值对角化以找到特征值。
the algorithm performs rapid diagonalizations of large sparse matrices.
该算法对大型稀疏矩阵执行快速对角化。
orthogonal diagonalizations are fundamental in principal component analysis.
正交对角化在主成分分析中是基础性的。
block diagonalizations effectively reduce the complexity of the system.
分块对角化有效地降低了系统的复杂性。
hermitian diagonalizations ensure that all eigenvalues are real numbers.
埃尔米特对角化确保所有特征值都是实数。
these theorems establish the necessary conditions for diagonalizations.
这些定理确立了对角化的必要条件。
cantor's diagonalizations proved that real numbers are uncountable.
康托尔的对角化证明了实数是不可数的。
effective diagonalizations require the matrix to have distinct eigenvectors.
有效的对角化需要矩阵具有不同的特征向量。
diagonalization argument
对角线论证
method of diagonalization
对角线化方法
diagonalization technique
对角线化技术
diagonalization proof
对角线化证明
diagonalization process
对角线化过程
diagonalization strategy
对角线化策略
performing diagonalization
执行对角线化
diagonalization algorithm
对角线化算法
diagonalization theorem
对角线化定理
matrix diagonalizations simplify the computation of matrix powers.
矩阵对角化简化了矩阵幂的计算。
simultaneous diagonalizations are possible if two matrices commute.
如果两个矩阵可以交换，那么可以同时对角化。
the proofs rely heavily on various abstract diagonalizations.
这些证明大量依赖于各种抽象的对角化。
we must perform numerical diagonalizations to find the eigenvalues.
我们必须进行数值对角化以找到特征值。
the algorithm performs rapid diagonalizations of large sparse matrices.
该算法对大型稀疏矩阵执行快速对角化。
orthogonal diagonalizations are fundamental in principal component analysis.
正交对角化在主成分分析中是基础性的。
block diagonalizations effectively reduce the complexity of the system.
分块对角化有效地降低了系统的复杂性。
hermitian diagonalizations ensure that all eigenvalues are real numbers.
埃尔米特对角化确保所有特征值都是实数。
these theorems establish the necessary conditions for diagonalizations.
这些定理确立了对角化的必要条件。
cantor's diagonalizations proved that real numbers are uncountable.
康托尔的对角化证明了实数是不可数的。
effective diagonalizations require the matrix to have distinct eigenvectors.
有效的对角化需要矩阵具有不同的特征向量。
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