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negative semidefinite matrix

半负定矩阵

本站译名 线性代数 义项编号TS-0026

中文别名
负半定矩阵

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How To Study As A Mathematics Major 封面

《How To Study As A Mathematics Major》 · 第 429-430 页 · Section 7.1「Characterizations and Properties of Hermitian Matrices」,定义段

A Hermitian matrix $A\in M_n$ is positive definite if $x^*Ax>0$ for all nonzero $x\in\mathbb C^n$; it is positive semidefinite if $x^*Ax\ge0$ for all nonzero $x\in\mathbb C^n$. The concepts negative definite and negative semidefinite may be defined for $A\in M_n$ by reversing the inequalities or, equivalently, by saying that $-A$ is positive definite or positive semidefinite, respectively.

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