Part V 多元函數微分學
多元函數微分的極限定義
\(設f(x,y)的定義域為D,P_0(x_0,y_0)是D的聚點(=內點+邊界點), \forall \epsilon>0,\exists \delta>0,當P(x,y)\in D \cap U(P_0, \delta )時,恆有|f(x,y)-A|<\epsilon \Rightarrow \lim_{x\to x_0 , y\to y_0}f(x,y)=A\)
多元函數微分的連續性
\(\lim_{x\to x_0 , y\to y_0}f(x,y)=f(x_0,y_0),則稱f(x,y)在(x_0,y_0)處連續\)
\(【注】\lim_{x\to x_0 , y\to y_0}f(x,y) \neq f(x_0,y_0),叫不連續,不討論間斷類型\)
多元函數微分的偏導數 z=f(x, y)
- \(\frac{\partial f }{\partial x}|\_{(x\_0,y\_0)}={f}'\_x(x\_0,y\_0) \underline{\underline{\triangle}}\lim_{\triangle x \to \infty}\frac{f(x\_0+\triangle x, y\_0)-f(x\_0,y\_0)}{\triangle x}\)
- \(\frac{\partial f }{\partial y}|\_{(x\_0,y\_0)}={f}'\_y(x\_0,y\_0) \underline{\underline{\triangle}}\lim\_{\triangle y \to \infty}\frac{f(x\_0, y\_0+\triangle y)-f(x\_0,y\_0)}{\triangle y}\)
多元函數微分-鏈式求導規則
\(設z=f(u,v,w), u=u(y), v=v(x,y), w=w(x)。稱x,y叫做自變量,u,v,w叫做中間變量,z叫因變量.\)
\(\frac{\partial z}{\partial x} = \frac{\partial z}{\partial v} \cdot \frac{\partial v}{\partial x} + \frac{\partial z}{\partial w} \cdot \frac{\partial w}{\partial x}\)
多元函數-高階偏導數
\(\frac{\partial z}{\partial x} = \frac{\partial z}{\partial v} \cdot \frac{\partial v}{\partial x} + \frac{\partial z}{\partial w} \cdot \frac{\partial w}{\partial x}\)
多元函數-無條件極值-必要條件
\(設z=f(x,y)在點(x_0, y_0)處\begin{cases} 一階偏導數存在\\ 取極值 \end{cases} ,則{f}'_x(x_0, y_0)=0,{f}'_y(x_0, y_0)=0\)
【注】適用於三元及以上(常考2-5元)
多元函數-無條件極值-充分條件
- Note:只適用於二元
多元函數-條件極值-求法
- 提法:\(求目標函數u=f(x,y,z)在約束條件\begin{cases} M (x,y,z)=0\\ N(x,y,z)=0 \end{cases} 下的極值\)
- 拉氏乘數法:
- \(構造輔助函數F(x,y,z,\lambda,\mu)=f(x,y,z)+\lambda M(x,y,z)+\mu N(x,y,z),(\lambda,\mu均可能取0)\)
- \(令{F}'(x)=0,{F}'(y)=0,{F}'(z)=0,{F}'(\lambda)=0,{F}'(\mu)=0\)
- \(解方程組 \Rightarrow P_i(x_i, y_i, z_i) \Rightarrow u(P_i),比較 \Rightarrow取最大、最小者為最大值,最小值\)