One kind of inverse eigenvalue problems, whose solutions are required to be normal or diagonalizable matrices, is investigated in quaternionic quantum mechanics.
摘要本文研究了四量子力学中一类要求其解是正规或可对角化四
阵的特征值反问题。
One kind of inverse eigenvalue problems, whose solutions are required to be normal or diagonalizable matrices, is investigated in quaternionic quantum mechanics.
摘要本文研究了四量子力学中一类要求其解是正规或可对角化四
阵的特征值反问题。
This paper discusses the structure, calculation of multiplication and power, eigenvalue and eigenvector, and diagonalizable problems of matrix of rank equal to 1.
摘要对秩等于1的阵的结构、乘法与乘幂运
、特征值与特征向量和对角化问题进行了讨论。
Each eigenstate of an observable corresponds to an eigenvector of the operator, and the associated eigenvalue corresponds to the value of the observable in that eigenstate.
每个可见特征值作者一特征向量,而相关的特征值
特征值里的可见值。
In the practical applications of highly nonnormal matrices, these theorems may be more useful than their generalized eigenvalue special cases and may provide more descriptive information.
在对高度非正规阵的研究应用中,这些定理将比它们的特例-广义特征值定理更可靠,能提供更多的信息。
声明:以上例句、词性分类均由互联网资源自动生成,部分未经过人工审核,其表达内容亦不代表本软件的观点;若发现问题,欢迎向我们指正。
One kind of inverse eigenvalue problems, whose solutions are required to be normal or diagonalizable matrices, is investigated in quaternionic quantum mechanics.
摘要本文研究了四元数量子力学中一类要求其解是正规或可对角化四元数矩反问题。
This paper discusses the structure, calculation of multiplication and power, eigenvalue and eigenvector, and diagonalizable problems of matrix of rank equal to 1.
摘要对秩等于1矩
结构、乘法与乘幂运
、
与
向量和对角化问题进行了讨论。
Each eigenstate of an observable corresponds to an eigenvector of the operator, and the associated eigenvalue corresponds to the value of the observable in that eigenstate.
每个可见符合操作者一
向量,而相关
符合
里
可见
。
In the practical applications of highly nonnormal matrices, these theorems may be more useful than their generalized eigenvalue special cases and may provide more descriptive information.
在对高度非正规矩研究应用中,这些定理将比它们
例-广义
定理更可靠,能提供更多
信息。
声明:以上例句、词性分类均由互联网资源自动生成,部分未经过人工审核,其表达内容亦不代表本软件观点;若发现问题,欢迎向我们指正。
One kind of inverse eigenvalue problems, whose solutions are required to be normal or diagonalizable matrices, is investigated in quaternionic quantum mechanics.
摘要本文研究了四元力学中一类要求其解是正规或可对角化四元
矩阵
特征
反问题。
This paper discusses the structure, calculation of multiplication and power, eigenvalue and eigenvector, and diagonalizable problems of matrix of rank equal to 1.
摘要对秩等于1矩阵
结构、乘法与乘幂运
、特征
与特征向
和对角化问题进行了讨论。
Each eigenstate of an observable corresponds to an eigenvector of the operator, and the associated eigenvalue corresponds to the value of the observable in that eigenstate.
每个可见特征符合操作者一特征向
,而相关
特征
符合特征
可见
。
In the practical applications of highly nonnormal matrices, these theorems may be more useful than their generalized eigenvalue special cases and may provide more descriptive information.
在对高度非正规矩阵研究应用中,这些定理将比它们
特例-广义特征
定理更可靠,能提供更多
信息。
声明:以上例句、词性分类均由互联网资源自动生成,部分未经过人工审核,其表达内容亦不代表本软件观点;若发现问题,欢迎向我们指正。
One kind of inverse eigenvalue problems, whose solutions are required to be normal or diagonalizable matrices, is investigated in quaternionic quantum mechanics.
摘要本文研究了四元数量子力学中一类要求其解是正规或可对角化四元数矩阵的特征值反问题。
This paper discusses the structure, calculation of multiplication and power, eigenvalue and eigenvector, and diagonalizable problems of matrix of rank equal to 1.
摘要对秩等于1的矩阵的结构、乘法与乘幂运、特征值与特征向量和对角化问题进行了讨论。
Each eigenstate of an observable corresponds to an eigenvector of the operator, and the associated eigenvalue corresponds to the value of the observable in that eigenstate.
每个可见特征值符合操作者一特征向量,而相关的特征值符合特征值里的可见值。
In the practical applications of highly nonnormal matrices, these theorems may be more useful than their generalized eigenvalue special cases and may provide more descriptive information.
在对高度非正规矩阵的研究应用中,这些定它们的特例-广义特征值定
更可靠,能提供更多的信息。
声明:以上例句、词性分类均由互联网资源自动生成,部分未经过人工审核,其表达内容亦不代表本软件的观点;若发现问题,欢迎向我们指正。
One kind of inverse eigenvalue problems, whose solutions are required to be normal or diagonalizable matrices, is investigated in quaternionic quantum mechanics.
摘本文研究
四元数量子力学中一类
求其解是正规或可
角化四元数矩阵的特征值反问题。
This paper discusses the structure, calculation of multiplication and power, eigenvalue and eigenvector, and diagonalizable problems of matrix of rank equal to 1.
摘等于1的矩阵的结构、乘法与乘幂运
、特征值与特征向量和
角化问题
讨论。
Each eigenstate of an observable corresponds to an eigenvector of the operator, and the associated eigenvalue corresponds to the value of the observable in that eigenstate.
每个可见特征值符合操作者一特征向量,而相关的特征值符合特征值里的可见值。
In the practical applications of highly nonnormal matrices, these theorems may be more useful than their generalized eigenvalue special cases and may provide more descriptive information.
在高度非正规矩阵的研究应用中,这些定理将比它们的特例-广义特征值定理更可靠,能提供更多的信息。
声明:以上例句、词性分类均由互联网资源自动生成,部分未经过人工审核,其表达内容亦不代表本软件的观点;若发现问题,欢迎向我们指正。
One kind of inverse eigenvalue problems, whose solutions are required to be normal or diagonalizable matrices, is investigated in quaternionic quantum mechanics.
摘要本文研究了四元数量子力学中一类要求其规或可对角化四元数矩阵的特征值反问题。
This paper discusses the structure, calculation of multiplication and power, eigenvalue and eigenvector, and diagonalizable problems of matrix of rank equal to 1.
摘要对秩等于1的矩阵的结构、乘法与乘幂运、特征值与特征向量和对角化问题进行了讨论。
Each eigenstate of an observable corresponds to an eigenvector of the operator, and the associated eigenvalue corresponds to the value of the observable in that eigenstate.
每个可见特征值符合操作者一特征向量,的特征值符合特征值里的可见值。
In the practical applications of highly nonnormal matrices, these theorems may be more useful than their generalized eigenvalue special cases and may provide more descriptive information.
在对高度非规矩阵的研究应用中,这些定理将比它们的特例-广义特征值定理更可靠,能提供更多的信息。
声明:以上例句、词性分类均由互联网资源自动生成,部分未经过人工审核,其表达内容亦不代表本软件的观点;若发现问题,欢迎向我们指。
One kind of inverse eigenvalue problems, whose solutions are required to be normal or diagonalizable matrices, is investigated in quaternionic quantum mechanics.
摘要本文研究了四元数量子力学中一类要求其解是正规或可对角化四元数矩阵的特征值。
This paper discusses the structure, calculation of multiplication and power, eigenvalue and eigenvector, and diagonalizable problems of matrix of rank equal to 1.
摘要对秩等于1的矩阵的结构、乘法与乘幂运、特征值与特征向量和对角化
进行了讨
。
Each eigenstate of an observable corresponds to an eigenvector of the operator, and the associated eigenvalue corresponds to the value of the observable in that eigenstate.
可见特征值符合操作者一特征向量,而相关的特征值符合特征值里的可见值。
In the practical applications of highly nonnormal matrices, these theorems may be more useful than their generalized eigenvalue special cases and may provide more descriptive information.
在对高度非正规矩阵的研究应用中,这些定理将比它们的特例-广义特征值定理更可靠,能提供更多的信息。
声明:以上例句、词性分类均由互联网资源自动生成,部分未经过人工审核,其表达内容亦不代表本软件的观点;若发现,欢迎向我们指正。
One kind of inverse eigenvalue problems, whose solutions are required to be normal or diagonalizable matrices, is investigated in quaternionic quantum mechanics.
摘要本文研究了四元数量中一类要求其解是正规或可对角化四元数矩阵的
反问题。
This paper discusses the structure, calculation of multiplication and power, eigenvalue and eigenvector, and diagonalizable problems of matrix of rank equal to 1.
摘要对秩等于1的矩阵的结构、乘法与乘幂运、
与
向量和对角化问题进行了讨论。
Each eigenstate of an observable corresponds to an eigenvector of the operator, and the associated eigenvalue corresponds to the value of the observable in that eigenstate.
每个可见符合操作者一
向量,而相关的
符合
里的可见
。
In the practical applications of highly nonnormal matrices, these theorems may be more useful than their generalized eigenvalue special cases and may provide more descriptive information.
在对高度非正规矩阵的研究应用中,这些定理将比它们的例-广义
定理更可靠,能提供更多的信息。
声明:以上例句、词性分类均由互联网资源自动生成,部分未经过人工审核,其表达内容亦不代表本软件的观点;若发现问题,欢迎向我们指正。
One kind of inverse eigenvalue problems, whose solutions are required to be normal or diagonalizable matrices, is investigated in quaternionic quantum mechanics.
摘要本文研究了四元数子力学中一类要求其解是
可对角化四元数矩阵的特征值反问题。
This paper discusses the structure, calculation of multiplication and power, eigenvalue and eigenvector, and diagonalizable problems of matrix of rank equal to 1.
摘要对秩等于1的矩阵的结构、乘法与乘幂运、特征值与特征
和对角化问题进行了讨论。
Each eigenstate of an observable corresponds to an eigenvector of the operator, and the associated eigenvalue corresponds to the value of the observable in that eigenstate.
每个可见特征值符合操作者一特征,
相关的特征值符合特征值里的可见值。
In the practical applications of highly nonnormal matrices, these theorems may be more useful than their generalized eigenvalue special cases and may provide more descriptive information.
在对高度非矩阵的研究应用中,这些定理将比它们的特例-广义特征值定理更可靠,能提供更多的信息。
声明:以上例句、词性分类均由互联网资源自动生成,部分未经过人工审核,其表达内容亦不代表本软件的观点;若发现问题,欢迎我们指
。