Partial Derivatives
For function f(x,y) and some point in the domain (x0,y0)∈D, we define derivatives of f(x,y) at (x0,y0) with respect to x as
fx(x0,y0)=Δx→0limΔxf(x0+Δx,y0)−f(x0,y0)=Δx→0limΔxΔw
which as also be denoted as (∂x∂w)(x0,y0)
When we extend this to even more variables, the full version looks like this:
fxj(a)=h→0limhf(a+hej)−f(a)
If f(⋅) is partially differentiable at every point in D, then we have the partial derivative function fx(⋅), also denoted as Dxjf(a)
我们可以用偏导数计算切于某点的平面,考虑 f:X↦R,X⊂R2,切于点 x=(a,b,f(a,b)) 的平面是
z=f(a,b)+fx(a,b)(x−a)+fy(a,b)(y−b)
Example 1. Suppose z=xy, prove that yx∂x∂z+lnx1∂y∂z=2z
Since z=xy, so
zx=yxy−1zy=xylnx
Substituting and we can prove the statement.
Second Order Partial Derivatives
If f’s k -th derivative exists and is continuous on D, then we denote f as a Ck function.
Proposition: ∂x∂y∂2f=∂y∂x∂2f⟺ f is a C2 function
Chain Rule for Partial Derivatives
For vector-valued functions, suppose h=f∘g,y0=g(t0), then
Dh(t0)=Df(y0)Dg(t0)
Total Differential
Δw≈dw=fx(x0,y0)dx+fy(x0,y0)dy