From 0b15d6de7efc2e55f0faf54c865c77368da6f395 Mon Sep 17 00:00:00 2001
From: unlockable <g@unlockableworld.com>
Date: Sat, 22 Apr 2023 17:43:53 +0800
Subject: [PATCH] =?UTF-8?q?=E6=94=B9=E9=94=99=E3=80=82?=
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---
 14多变量函数的微分学.tex | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/14多变量函数的微分学.tex b/14多变量函数的微分学.tex
index 0708822..e7bb3b7 100644
--- a/14多变量函数的微分学.tex
+++ b/14多变量函数的微分学.tex
@@ -540,7 +540,7 @@ J_y \bvec{F} = \begin{bmatrix}
 
 根据这个定理，我们可以引入Lagrange乘数法。定义函数$L: D \times \realnum^m \to \realnum$，
 \[L(\bvec{z}, \bvec{\Lambda}) = f(\bvec{z}) + \bvec{\lambda} \Phi(\bvec{z}), (\bvec{z}, \bvec{\Lambda}) \in D \times \realnum^m\]
-$L$称为条件极值问题的Lagrange函数，$\bvec{\Lambda}$称为Lagrange乘数/乘子。根据条件极值的表要条件，在条件极值点$\bvec{z}_0 \in D$，存在$\bvec{\Lambda} \in \realnum^m$满足
+$L$称为条件极值问题的Lagrange函数，$\bvec{\Lambda}$称为Lagrange乘数/乘子。根据条件极值的必要条件，在条件极值点$\bvec{z}_0 \in D$，存在$\bvec{\Lambda} \in \realnum^m$满足
 \[J_{\bvec{z}} L (\bvec{z}_0, \bvec{\Lambda}) = J_{\bvec{z}} f(\bvec{z}_0) + \bvec{\Lambda} J_{\bvec{z}}\Phi(\bvec{z}_0) = \bvec{0}\]
 此外
 \[J_{\bvec{\Lambda}} L(\bvec{z}_0, \bvec{\Lambda}) = \Phi(\bvec{z}_0) = \bvec{0}\]