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Matrix norm : ウィキペディア英語版
Matrix norm
In mathematics, a matrix norm is a natural extension of the notion of a vector norm to matrices.
== Definition ==

In what follows, K will denote the field of real or complex numbers. Let K^ denote the vector space containing all matrices with m rows and n columns with entries in K. Throughout, A^
* denotes the conjugate transpose of matrix A.
A matrix norm is a vector norm on K^. That is, if \|A\| denotes the norm of the matrix A, then,
*\|A\|\ge 0
*\|A\|= 0 iff A=0
*\|\alpha A\|=|\alpha| \|A\| for all \alpha in K and all matrices A in K^
*\|A+B\| \le \|A\|+\|B\| for all matrices A and B in K^.
Additionally, in the case of square matrices (thus, ''m'' = ''n''), some (but not all) matrix norms satisfy the following condition, which is related to the fact that matrices are more than just vectors:
*\|AB\| \le \|A\|\|B\| for all matrices A and B in K^.
A matrix norm that satisfies this additional property is called a sub-multiplicative norm (in some books, the terminology ''matrix norm'' is used only for those norms which are sub-multiplicative). The set of all ''n''-by-''n'' matrices, together with such a sub-multiplicative norm, is an example of a Banach algebra.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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