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DAY01:【ML 第二弹】高等数学

1、导数的定义

f ′ ( x 0 ) = lim ⁡ Δ x → 0 f ( x 0 + Δ x ) − f ( x 0 ) Δ x f'(x_0) = \lim_{\Delta x \to 0} \frac{f(x_0 + \Delta x) - f(x_0)}{\Delta x} \quad f(x0)=Δx0limΔxf(x0+Δx)f(x0)

f ′ ( x 0 ) = lim ⁡ x → x 0 f ( x ) − f ( x 0 ) x − x 0 f'(x_0) = \lim_{x \to x_0} \frac{f(x) - f(x_0)}{x - x_0} \quad f(x0)=xx0limxx0f(x)f(x0)

2、左/右导数的几何意义和物理意义

函数 f ( x ) f(x) f(x) x 0 x_{0} x0处的左、右导数分别定义为:

2.1 左导数

f − ′ ( x 0 ) = lim ⁡ Δ x → 0 − f ( x 0 + Δ x ) − f ( x 0 ) Δ x = lim ⁡ x → x 0 − f ( x ) − f ( x 0 ) x − x 0 , ( x = x 0 + Δ x ) f'_-(x_0) = \lim_{\Delta x \to 0^-} \frac{f(x_0 + \Delta x) - f(x_0)}{\Delta x} = \lim_{x \to x_0^-} \frac{f(x) - f(x_0)}{x - x_0}, \, (x = x_0 + \Delta x) f(x0)=Δx0limΔxf(x0+Δx)f(x0)=xx0limxx0f(x)f(x0),(x=x0+Δx)

2.2 右导数

f + ′ ( x 0 ) = lim ⁡ Δ x → 0 + f ( x 0 + Δ x ) − f ( x 0 ) Δ x = lim ⁡ x → x 0 + f ( x ) − f ( x 0 ) x − x 0 f'_+(x_0) = \lim_{\Delta x \to 0^+} \frac{f(x_0 + \Delta x) - f(x_0)}{\Delta x} = \lim_{x \to x_0^+} \frac{f(x) - f(x_0)}{x - x_0} f+(x0)=Δx0+limΔxf(x0+Δx)f(x0)=xx0+limxx0f(x)f(x0)

3、函数的可导性与连续性之间的关系

(1)函数 f ( x ) f(x) f(x) x 0 x_0 x0处可微 ⇔ \Leftrightarrow f ( x ) f(x) f(x) x 0 x_0 x0处可导。
(2)若函数在点 x 0 x_0 x0处可导,则 y = f ( x ) y = f(x) y=f(x)在点 x 0 x_0 x0处连续,反之则不成立,即函数连续不一定可导。
(3) f ′ ( x 0 ) f'(x_0) f(x0)存在 ⇔ \Leftrightarrow f − ′ ( x 0 ) = f + ′ ( x 0 ) f'_-(x_0) = f'_+(x_0) f(x0)=f+(x0)

4、平面曲线的切线和法线

4.1 切线方程

y − y 0 = f ′ ( x 0 ) ( x − x 0 ) y - y_0 = f'(x_0)(x - x_0) yy0=f(x0)(xx0)

4.2 法线方程

y − y 0 = − 1 f ′ ( x 0 ) ( x − x 0 ) , f ′ ( x 0 ) ≠ 0 y - y_0 = -\frac{1}{f'(x_0)}(x - x_0), \, f'(x_0) \neq 0 yy0=f(x0)1(xx0),f(x0)=0

5、四则运算

设函数 u = u ( x ) u = u(x) u=u(x) v = v ( x ) v = v(x) v=v(x)在点 x x x可导,则:
(1) ( u ± v ) ′ = u ′ ± v ′ (u \pm v)' = u' \pm v' (u±v)=u±v
(2) ( u v ) ′ = u v ′ + v u ′ (uv)' = uv' + vu' (uv)=uv+vu d ( u v ) = u d v + v d u d(uv) = udv + vdu d(uv)=udv+vdu
(3) ( u v ) ′ = v u ′ − u v ′ v 2 ( v ≠ 0 ) \left( \frac{u}{v} \right)' = \frac{vu' - uv'}{v^2} \, (v \neq 0) (vu)=v2vuuv(v=0) d ( u v ) = v d u − u d v v 2 d\left( \frac{u}{v} \right) = \frac{vdu - udv}{v^2} d(vu)=v2vduudv

6、基本导数与微分表

序号函数 y y y导数 y ′ y' y微分 d y dy dy
1 y = c y = c y=c(常数) 0 0 0 0 0 0
2 y = x α y = x^\alpha y=xα α \alpha α 为实数) α x α − 1 \alpha x^{\alpha-1} αxα1 α x α − 1 d x \alpha x^{\alpha-1} dx αxα1dx
3 y = a x y = a^x y=ax a x ln ⁡ a a^x \ln a axlna a x ln ⁡ a d x a^x \ln a dx axlnadx
特例: y = e x y = e^x y=ex e x e^x ex e x d x e^x dx exdx
4 y = log ⁡ a x y = \log_a x y=logax 1 x ln ⁡ a \frac{1}{x \ln a} xlna1 1 x ln ⁡ a d x \frac{1}{x \ln a} dx xlna1dx
特例: y = ln ⁡ x y = \ln x y=lnx 1 x \frac{1}{x} x1 1 x d x \frac{1}{x} dx x1dx
5 y = sin ⁡ x y = \sin x y=sinx cos ⁡ x \cos x cosx cos ⁡ x d x \cos x dx cosxdx
6 y = cos ⁡ x y = \cos x y=cosx − sin ⁡ x -\sin x sinx − sin ⁡ x d x -\sin x dx sinxdx
7 y = tan ⁡ x y = \tan x y=tanx sec ⁡ 2 x \sec^2 x sec2x(或 1 cos ⁡ 2 x \frac{1}{\cos^2 x} cos2x1 sec ⁡ 2 x d x \sec^2 x dx sec2xdx
8 y = cot ⁡ x y = \cot x y=cotx − csc ⁡ 2 x -\csc^2 x csc2x(或 − 1 sin ⁡ 2 x -\frac{1}{\sin^2 x} sin2x1 − csc ⁡ 2 x d x -\csc^2 x dx csc2xdx
9 y = sec ⁡ x y = \sec x y=secx sec ⁡ x tan ⁡ x \sec x \tan x secxtanx sec ⁡ x tan ⁡ x d x \sec x \tan x dx secxtanxdx
10 y = csc ⁡ x y = \csc x y=cscx − csc ⁡ x cot ⁡ x -\csc x \cot x cscxcotx − csc ⁡ x cot ⁡ x d x -\csc x \cot x dx cscxcotxdx
11 y = arcsin ⁡ x y = \arcsin x y=arcsinx 1 1 − x 2 \frac{1}{\sqrt{1-x^2}} 1x2 1 1 1 − x 2 d x \frac{1}{\sqrt{1-x^2}} dx 1x2 1dx
12 y = arccos ⁡ x y = \arccos x y=arccosx − 1 1 − x 2 -\frac{1}{\sqrt{1-x^2}} 1x2 1 − 1 1 − x 2 d x -\frac{1}{\sqrt{1-x^2}} dx 1x2 1dx
13 y = arctan ⁡ x y = \arctan x y=arctanx 1 1 + x 2 \frac{1}{1+x^2} 1+x21 1 1 + x 2 d x \frac{1}{1+x^2} dx 1+x21dx
14 y = arccot ⁡ x y = \operatorname{arccot} x y=arccotx − 1 1 + x 2 -\frac{1}{1+x^2} 1+x21 − 1 1 + x 2 d x -\frac{1}{1+x^2} dx 1+x21dx
15 y = sh ⁡ x y = \operatorname{sh} x y=shx(双曲正弦) ch ⁡ x \operatorname{ch} x chx(双曲余弦) ch ⁡ x d x \operatorname{ch} x dx chxdx
16 y = ch ⁡ x y = \operatorname{ch}x y=chx sh ⁡ x \operatorname{sh}x shx sh ⁡ x d x \operatorname{sh}x \, dx shxdx

7、复合函数,反函数,隐函数的微分法

7.1 复合函数

μ = φ ( x ) \mu = \varphi(x) μ=φ(x)在点 x x x可导,而 y = f ( μ ) y = f(\mu) y=f(μ)在对应点 μ \mu μ μ = φ ( x ) \mu = \varphi(x) μ=φ(x))可导,则复合函数 y = f ( φ ( x ) ) y = f(\varphi(x)) y=f(φ(x))在点 x x x可导,且:
y ′ = f ′ ( μ ) ⋅ φ ′ ( x ) y' = f'(\mu) \cdot \varphi'(x) y=f(μ)φ(x)

7.2 反函数

y = f ( x ) y = f(x) y=f(x)在点 x x x的某邻域内单调连续,在点 x x x处可导且 f ′ ( x ) ≠ 0 f'(x) \neq 0 f(x)=0,则其反函数在点 x x x所对应的 y y y处可导,且:
d y d x = 1 d x d y \frac{dy}{dx} = \frac{1}{\frac{dx}{dy}} dxdy=dydx1

7.3 隐函数导数 d y d x \frac{dy}{dx} dxdy

(1)方程两边对 x x x求导:

y y y x x x的函数,则 y y y的函数(如 1 y \frac{1}{y} y1 y 2 y^2 y2 ln ⁡ y \ln y lny e y e^y ey 等)是 x x x的复合函数,对 x x x求导需按复合函数连锁法则进行。

(2)公式法:

F ( x , y ) = 0 F(x, y) = 0 F(x,y)=0知:
d y d x = − F x ′ ( x , y ) F y ′ ( x , y ) \frac{dy}{dx} = -\frac{F'_x(x, y)}{F'_y(x, y)} dxdy=Fy(x,y)Fx(x,y)
其中, F x ′ ( x , y ) F'_x(x, y) Fx(x,y) F y ′ ( x , y ) F'_y(x, y) Fy(x,y) 分别表示 F ( x , y ) F(x, y) F(x,y) x x x y y y的偏导数。

(3)利用微分形式不变性

8、常用高阶导数公式

(1) ( a x ) ( n ) = a x ln ⁡ n a ( a > 0 ) (a^x)^{(n)} = a^x \ln^n a \quad (a > 0) (ax)(n)=axlnna(a>0) ( e x ) ( n ) = e x (e^x)^{(n)} = e^x (ex)(n)=ex
(2) ( sin ⁡ k x ) ( n ) = k n sin ⁡ ( k x + n ⋅ π 2 ) (\sin kx)^{(n)} = k^n \sin\left(kx + n \cdot \frac{\pi}{2}\right) (sinkx)(n)=knsin(kx+n2π)
(3) ( cos ⁡ k x ) ( n ) = k n cos ⁡ ( k x + n ⋅ π 2 ) (\cos kx)^{(n)} = k^n \cos\left(kx + n \cdot \frac{\pi}{2}\right) (coskx)(n)=kncos(kx+n2π)
(4) ( x m ) ( n ) = m ( m − 1 ) ⋯ ( m − n + 1 ) x m − n (x^m)^{(n)} = m(m-1)\cdots(m-n+1)x^{m-n} (xm)(n)=m(m1)(mn+1)xmn
(5) ( ln ⁡ x ) ( n ) = ( − 1 ) n − 1 ( n − 1 ) ! x n (\ln x)^{(n)} = (-1)^{n-1} \frac{(n-1)!}{x^n} (lnx)(n)=(1)n1xn(n1)!
(6)莱布尼兹公式:若 u ( x ) , v ( x ) u(x), v(x) u(x),v(x) n n n阶可导,则:
( u v ) ( n ) = ∑ i = 0 n c n i u ( i ) v ( n − i ) (uv)^{(n)} = \sum_{i=0}^n c_{n}^{i} u^{(i)} v^{(n-i)} (uv)(n)=i=0ncniu(i)v(ni)
其中 u ( 0 ) = u u^{(0)} = u u(0)=u v ( 0 ) = v v^{(0)} = v v(0)=v

9、微分中值定理

9.1 费马定理

若函数 f ( x ) f(x) f(x)满足条件:

  1. 函数 f ( x ) f(x) f(x) x 0 x_0 x0的某邻域内有定义,并且在此邻域内恒有 f ( x ) ≤ f ( x 0 ) f(x) \leq f(x_0) f(x)f(x0) f ( x ) ≥ f ( x 0 ) f(x) \geq f(x_0) f(x)f(x0)
  2. f ( x ) f(x) f(x) x 0 x_0 x0处可导,则有 f ′ ( x 0 ) = 0 f'(x_0) = 0 f(x0)=0

9.2 罗尔定理

设函数 f ( x ) f(x) f(x)满足条件:

  1. 在闭区间 [ a , b ] [a, b] [a,b]上连续
  2. ( a , b ) (a, b) (a,b)内可导
  3. f ( a ) = f ( b ) f(a) = f(b) f(a)=f(b),则在 ( a , b ) (a, b) (a,b)内存在一个 ξ \xi ξ,使 f ′ ( ξ ) = 0 f'(\xi) = 0 f(ξ)=0

9.3 拉格朗日中值定理

设函数 f ( x ) f(x) f(x)满足条件:

  1. [ a , b ] [a, b] [a,b]上连续
  2. ( a , b ) (a, b) (a,b)内可导,则在 ( a , b ) (a, b) (a,b)内存在一个 ξ \xi ξ,使 f ( b ) − f ( a ) b − a = f ′ ( ξ ) \frac{f(b) - f(a)}{b - a} = f'(\xi) baf(b)f(a)=f(ξ)

9.4 柯西中值定理

设函数 f ( x ) f(x) f(x) g ( x ) g(x) g(x)满足条件:

  1. [ a , b ] [a, b] [a,b]上连续
  2. ( a , b ) (a, b) (a,b)内可导且 f ′ ( x ) f'(x) f(x) g ′ ( x ) g'(x) g(x)均存在,且 g ′ ( x ) ≠ 0 g'(x) \neq 0 g(x)=0,则在 ( a , b ) (a, b) (a,b)内存在一个 ξ \xi ξ,使 f ( b ) − f ( a ) g ( b ) − g ( a ) = f ′ ( ξ ) g ′ ( ξ ) \frac{f(b) - f(a)}{g(b) - g(a)} = \frac{f'(\xi)}{g'(\xi)} g(b)g(a)f(b)f(a)=g(ξ)f(ξ)

10、洛必达法则

10.1 法则Ⅰ( 0 0 \frac{0}{0} 00型不定式极限)

设函数 f ( x ) f(x) f(x) g ( x ) g(x) g(x)满足:

  • lim ⁡ x → x 0 f ( x ) = 0 \lim_{x \to x_0} f(x) = 0 limxx0f(x)=0 lim ⁡ x → x 0 g ( x ) = 0 \lim_{x \to x_0} g(x) = 0 limxx0g(x)=0
  • f , g f,g fg x 0 x_0 x0邻域可导( x 0 x_0 x0处除外),且 g ′ ( x ) ≠ 0 g'(x) \neq 0 g(x)=0
  • lim ⁡ x → x 0 f ′ ( x ) g ′ ( x ) \lim_{x \to x_0} \frac{f'(x)}{g'(x)} limxx0g(x)f(x)存在(或 ∞ \infty
    则:
    lim ⁡ x → x 0 f ( x ) g ( x ) = lim ⁡ x → x 0 f ′ ( x ) g ′ ( x ) \lim_{x \to x_0} \frac{f(x)}{g(x)} = \lim_{x \to x_0} \frac{f'(x)}{g'(x)} xx0limg(x)f(x)=xx0limg(x)f(x)

10.2 法则Ⅰ’( 0 0 \frac{0}{0} 00型, x → ∞ x \to \infty x情形)

f , g f,g fg满足:

  • lim ⁡ x → ∞ f ( x ) = lim ⁡ x → ∞ g ( x ) = 0 \lim_{x \to \infty} f(x) = \lim_{x \to \infty} g(x) = 0 limxf(x)=limxg(x)=0
  • ∣ x ∣ > X |x| > X x>X f , g f,g fg可导, g ′ ( x ) ≠ 0 g'(x) \neq 0 g(x)=0
  • lim ⁡ x → ∞ f ′ ( x ) g ′ ( x ) \lim_{x \to \infty} \frac{f'(x)}{g'(x)} limxg(x)f(x)存在(或 ∞ \infty
    则:
    lim ⁡ x → ∞ f ( x ) g ( x ) = lim ⁡ x → ∞ f ′ ( x ) g ′ ( x ) \lim_{x \to \infty} \frac{f(x)}{g(x)} = \lim_{x \to \infty} \frac{f'(x)}{g'(x)} xlimg(x)f(x)=xlimg(x)f(x)

10.3 法则Ⅱ( ∞ ∞ \frac{\infty}{\infty} 型不定式极限)

f , g f,g fg满足:

  • lim ⁡ x → x 0 f ( x ) = lim ⁡ x → x 0 g ( x ) = ∞ \lim_{x \to x_0} f(x) = \lim_{x \to x_0} g(x) = \infty limxx0f(x)=limxx0g(x)=
  • f , g f,g fg x 0 x_0 x0邻域可导( x 0 x_0 x0处除外),且 g ′ ( x ) ≠ 0 g'(x) \neq 0 g(x)=0
  • lim ⁡ x → x 0 f ′ ( x ) g ′ ( x ) \lim_{x \to x_0} \frac{f'(x)}{g'(x)} limxx0g(x)f(x)存在(或 ∞ \infty
    则:
    lim ⁡ x → x 0 f ( x ) g ( x ) = lim ⁡ x → x 0 f ′ ( x ) g ′ ( x ) \lim_{x \to x_0} \frac{f(x)}{g(x)} = \lim_{x \to x_0} \frac{f'(x)}{g'(x)} xx0limg(x)f(x)=xx0limg(x)f(x)

10.4 法则Ⅱ’( ∞ ∞ \frac{\infty}{\infty} 型, x → ∞ x \to \infty x情形)

同理法则Ⅰ’,将 x → x 0 x \to x_0 xx0替换为 x → ∞ x \to \infty x即可(条件类似)

11、泰勒公式

设函数 f ( x ) f(x) f(x) x 0 x_0 x0的某邻域内具有 n + 1 n+1 n+1阶导数,则对该邻域内异于 x 0 x_0 x0的任意 x x x,存在 ξ \xi ξ(介于 x 0 x_0 x0 x x x之间),使得:
f ( x ) = f ( x 0 ) + f ′ ( x 0 ) ( x − x 0 ) + f ′ ′ ( x 0 ) 2 ! ( x − x 0 ) 2 + ⋯ + f ( n ) ( x 0 ) n ! ( x − x 0 ) n + R n ( x ) ⋯ f(x) = f(x_0) + f'(x_0)(x-x_0) + \frac{f''(x_0)}{2!}(x-x_0)^2 + \cdots + \frac{f^{(n)}(x_0)}{n!}(x-x_0)^n + R_n(x) \cdots f(x)=f(x0)+f(x0)(xx0)+2!f′′(x0)(xx0)2++n!f(n)(x0)(xx0)n+Rn(x)
其中余项 R n ( x ) = f ( n + 1 ) ( ξ ) ( n + 1 ) ! ( x − x 0 ) n + 1 R_n(x) = \frac{f^{(n+1)}(\xi)}{(n+1)!}(x-x_0)^{n+1} Rn(x)=(n+1)!f(n+1)(ξ)(xx0)n+1称为 f ( x ) f(x) f(x)在点 x 0 x_0 x0处的 n n n阶泰勒余项

麦克劳林公式( x 0 = 0 x_0 = 0 x0=0时的泰勒公式)

f ( x ) = f ( 0 ) + f ′ ( 0 ) x + f ′ ′ ( 0 ) 2 ! x 2 + ⋯ + f ( n ) ( 0 ) n ! x n + R n ( x ) f(x) = f(0) + f'(0)x + \frac{f''(0)}{2!}x^2 + \cdots + \frac{f^{(n)}(0)}{n!}x^n + R_n(x) f(x)=f(0)+f(0)x+2!f′′(0)x2++n!f(n)(0)xn+Rn(x)
余项 R n ( x ) = f ( n + 1 ) ( ξ ) ( n + 1 ) ! x n + 1 R_n(x) = \frac{f^{(n+1)}(\xi)}{(n+1)!}x^{n+1} Rn(x)=(n+1)!f(n+1)(ξ)xn+1 ξ \xi ξ介于 0 0 0 x x x之间)

常用函数的麦克劳林公式(带余项)

  1. 指数函数 e x e^x ex
    e x = 1 + x + 1 2 ! x 2 + ⋯ + 1 n ! x n + x n + 1 ( n + 1 ) ! e ξ ( ξ 介于  0 与  x 之间 ) e^x = 1 + x + \frac{1}{2!}x^2 + \cdots + \frac{1}{n!}x^n + \frac{x^{n+1}}{(n+1)!}e^\xi \quad (\xi \text{ 介于 } 0 \text{ 与 } x \text{ 之间}) ex=1+x+2!1x2++n!1xn+(n+1)!xn+1eξ(ξ 介于 0  x 之间)

    e x = 1 + x + 1 2 ! x 2 + ⋯ + 1 n ! x n + o ( x n ) e^x = 1 + x + \frac{1}{2!}x^2 + \cdots + \frac{1}{n!}x^n + o(x^n) ex=1+x+2!1x2++n!1xn+o(xn)
  2. 正弦函数 sin ⁡ x \sin x sinx
    sin ⁡ x = x − 1 3 ! x 3 + ⋯ + x n n ! sin ⁡ n π 2 + x n + 1 ( n + 1 ) ! sin ⁡ ( ξ + n + 1 2 π ) \sin x = x - \frac{1}{3!}x^3 + \cdots + \frac{x^n}{n!}\sin\frac{n\pi}{2} + \frac{x^{n+1}}{(n+1)!}\sin\left(\xi + \frac{n+1}{2}\pi\right) sinx=x3!1x3++n!xnsin2+(n+1)!xn+1sin(ξ+2n+1π)

    sin ⁡ x = x − 1 3 ! x 3 + ⋯ + x n n ! sin ⁡ n π 2 + o ( x n ) \sin x = x - \frac{1}{3!}x^3 + \cdots + \frac{x^n}{n!}\sin\frac{n\pi}{2} + o(x^n) sinx=x3!1x3++n!xnsin2+o(xn)
  3. 余弦函数 cos ⁡ x \cos x cosx
    cos ⁡ x = 1 − 1 2 ! x 2 + ⋯ + x n n ! cos ⁡ n π 2 + x n + 1 ( n + 1 ) ! cos ⁡ ( ξ + n + 1 2 π ) \cos x = 1 - \frac{1}{2!}x^2 + \cdots + \frac{x^n}{n!}\cos\frac{n\pi}{2} + \frac{x^{n+1}}{(n+1)!}\cos\left(\xi + \frac{n+1}{2}\pi\right) cosx=12!1x2++n!xncos2+(n+1)!xn+1cos(ξ+2n+1π)

    cos ⁡ x = 1 − 1 2 ! x 2 + ⋯ + x n n ! cos ⁡ n π 2 + o ( x n ) \cos x = 1 - \frac{1}{2!}x^2 + \cdots + \frac{x^n}{n!}\cos\frac{n\pi}{2} + o(x^n) cosx=12!1x2++n!xncos2+o(xn)
  4. 对数函数 ln ⁡ ( 1 + x ) \ln(1+x) ln(1+x)
    ln ⁡ ( 1 + x ) = x − 1 2 x 2 + 1 3 x 3 − ⋯ + ( − 1 ) n − 1 x n n + ( − 1 ) n x n + 1 ( n + 1 ) ( 1 + ξ ) n + 1 \ln(1+x) = x - \frac{1}{2}x^2 + \frac{1}{3}x^3 - \cdots + (-1)^{n-1}\frac{x^n}{n} + \frac{(-1)^n x^{n+1}}{(n+1)(1+\xi)^{n+1}} ln(1+x)=x21x2+31x3+(1)n1nxn+(n+1)(1+ξ)n+1(1)nxn+1

    ln ⁡ ( 1 + x ) = x − 1 2 x 2 + 1 3 x 3 − ⋯ + ( − 1 ) n − 1 x n n + o ( x n ) \ln(1+x) = x - \frac{1}{2}x^2 + \frac{1}{3}x^3 - \cdots + (-1)^{n-1}\frac{x^n}{n} + o(x^n) ln(1+x)=x21x2+31x3+(1)n1nxn+o(xn)
  5. 幂函数 ( 1 + x ) m (1+x)^m (1+x)m
    ( 1 + x ) m = 1 + m x + m ( m − 1 ) 2 ! x 2 + ⋯ + m ( m − 1 ) ⋯ ( m − n + 1 ) n ! x n + m ( m − 1 ) ⋯ ( m − n ) ( n + 1 ) ! x n + 1 ( 1 + ξ ) m − n − 1 (1+x)^m = 1 + mx + \frac{m(m-1)}{2!}x^2 + \cdots + \frac{m(m-1)\cdots(m-n+1)}{n!}x^n + \frac{m(m-1)\cdots(m-n)}{(n+1)!}x^{n+1}(1+\xi)^{m-n-1} (1+x)m=1+mx+2!m(m1)x2++n!m(m1)(mn+1)xn+(n+1)!m(m1)(mn)xn+1(1+ξ)mn1

    ( 1 + x ) m = 1 + m x + m ( m − 1 ) 2 ! x 2 + ⋯ + m ( m − 1 ) ⋯ ( m − n + 1 ) n ! x n + o ( x n ) (1+x)^m = 1 + mx + \frac{m(m-1)}{2!}x^2 + \cdots + \frac{m(m-1)\cdots(m-n+1)}{n!}x^n + o(x^n) (1+x)m=1+mx+2!m(m1)x2++n!m(m1)(mn+1)xn+o(xn)

12、函数单调性的判断

12.1 判定定理

设函数 f ( x ) f(x) f(x)在区间 ( a , b ) (a, b) (a,b)内可导,若对于任意 x ∈ ( a , b ) x \in (a, b) x(a,b),都有 f ′ ( x ) > 0 f'(x) > 0 f(x)>0(或 f ′ ( x ) < 0 f'(x) < 0 f(x)<0),则函数 f ( x ) f(x) f(x) ( a , b ) (a, b) (a,b)内是单调增加的(或单调减少)

12.2 取极值的必要条件

设函数 f ( x ) f(x) f(x) x 0 x_0 x0处可导,且在 x 0 x_0 x0处取极值,则 f ′ ( x 0 ) = 0 f'(x_0) = 0 f(x0)=0

12.3 取极值的第一充分条件

设函数 f ( x ) f(x) f(x) x 0 x_0 x0的某一邻域内可微,且 f ′ ( x 0 ) = 0 f'(x_0) = 0 f(x0)=0(或 f ( x ) f(x) f(x) x 0 x_0 x0处连续,但 f ′ ( x 0 ) f'(x_0) f(x0)不存在):

  1. 若当 x x x经过 x 0 x_0 x0时, f ′ ( x ) f'(x) f(x)由“+”变“-”,则 f ( x 0 ) f(x_0) f(x0)为极大值
  2. 若当 x x x经过 x 0 x_0 x0时, f ′ ( x ) f'(x) f(x)由“-”变“+”,则 f ( x 0 ) f(x_0) f(x0)为极小值
  3. f ′ ( x ) f'(x) f(x)经过 x = x 0 x = x_0 x=x0的两侧不变号,则 f ( x 0 ) f(x_0) f(x0)不是极值

12.4 取极值的第二充分条件

f ( x ) f(x) f(x)在点 x 0 x_0 x0处有 f ′ ′ ( x ) ≠ 0 f''(x) \neq 0 f′′(x)=0,且 f ′ ( x 0 ) = 0 f'(x_0) = 0 f(x0)=0,则:

  • f ′ ′ ( x 0 ) < 0 f''(x_0) < 0 f′′(x0)<0时, f ( x 0 ) f(x_0) f(x0)为极大值
  • f ′ ′ ( x 0 ) > 0 f''(x_0) > 0 f′′(x0)>0时, f ( x 0 ) f(x_0) f(x0)为极小值

注:如果 f ′ ′ ( x 0 ) = 0 f''(x_0) = 0 f′′(x0)=0,此方法失效

13、渐近线的求解

13.1 水平渐近线

lim ⁡ x → + ∞ f ( x ) = b 或 lim ⁡ x → − ∞ f ( x ) = b \lim_{x \to +\infty} f(x) = b \quad \text{或} \quad \lim_{x \to -\infty} f(x) = b limx+f(x)=blimxf(x)=b,则 y = b y = b y=b称为函数 y = f ( x ) y = f(x) y=f(x)的水平渐近线

13.2 铅直渐近线

lim ⁡ x → x 0 − f ( x ) = ∞ 或 lim ⁡ x → x 0 + f ( x ) = ∞ \lim_{x \to x_0^-} f(x) = \infty \quad \text{或} \quad \lim_{x \to x_0^+} f(x) = \infty limxx0f(x)=limxx0+f(x)=,则 x = x 0 x = x_0 x=x0称为 y = f ( x ) y = f(x) y=f(x)的铅直渐近线

13.3 斜渐近线

a = lim ⁡ x → ∞ f ( x ) x , b = lim ⁡ x → ∞ [ f ( x ) − a x ] a = \lim_{x \to \infty} \frac{f(x)}{x}, \quad b = \lim_{x \to \infty} [f(x) - ax] a=limxxf(x),b=limx[f(x)ax],则 y = a x + b y = ax + b y=ax+b称为 y = f ( x ) y = f(x) y=f(x)的斜渐近线

14、函数凹凸性的判断

14.1 凹凸性判别定理

若在区间 I I I f ′ ′ ( x ) < 0 f''(x) < 0 f′′(x)<0(或 f ′ ′ ( x ) > 0 f''(x) > 0 f′′(x)>0),则 f ( x ) f(x) f(x) I I I上是的(或的)

14.2 拐点判别定理(第一充分条件)

若在 x 0 x_0 x0 f ′ ′ ( x 0 ) = 0 f''(x_0) = 0 f′′(x0)=0(或 f ′ ′ ( x 0 ) f''(x_0) f′′(x0)不存在),且当 x x x经过 x 0 x_0 x0时, f ′ ′ ( x ) f''(x) f′′(x)变号,则 ( x 0 , f ( x 0 ) ) (x_0, f(x_0)) (x0,f(x0))拐点

14.3 拐点判别定理(第二充分条件)

f ( x ) f(x) f(x) x 0 x_0 x0点的某邻域内有三阶导数,且 f ′ ′ ( x 0 ) = 0 f''(x_0) = 0 f′′(x0)=0 f ′ ′ ′ ( x 0 ) ≠ 0 f'''(x_0) \neq 0 f′′′(x0)=0,则 ( x 0 , f ( x 0 ) ) (x_0, f(x_0)) (x0,f(x0))拐点

15、弧微分

d S = 1 + y ′ 2 d x dS = \sqrt{1 + y'^2} \, dx dS=1+y′2 dx

16、曲率

16.1 显函数形式 y = f ( x ) y = f(x) y=f(x)

曲线在点 ( x , y ) (x, y) (x,y)处的曲率 k k k为:
k = ∣ y ′ ′ ∣ ( 1 + y ′ 2 ) 3 / 2 k = \frac{|y''|}{(1 + y'^2)^{3/2}} k=(1+y′2)3/2y′′

16.2 参数方程形式 { x = φ ( t ) y = ψ ( t ) \begin{cases} x = \varphi(t) \\ y = \psi(t) \end{cases} {x=φ(t)y=ψ(t)

曲线的曲率 k k k为:
k = ∣ φ ′ ( t ) ψ ′ ′ ( t ) − φ ′ ′ ( t ) ψ ′ ( t ) ∣ [ φ ′ 2 ( t ) + ψ ′ 2 ( t ) ] 3 / 2 k = \frac{|\varphi'(t)\psi''(t) - \varphi''(t)\psi'(t)|}{[\varphi'^2(t) + \psi'^2(t)]^{3/2}} k=[φ′2(t)+ψ′2(t)]3/2φ(t)ψ′′(t)φ′′(t)ψ(t)

17、曲率半径

曲线在点 M M M处的曲率 k k k k ≠ 0 k \neq 0 k=0)与曲率半径 ρ \rho ρ的关系为:
ρ = 1 k \rho = \frac{1}{k} ρ=k1


微语录:你有那么多的以后,却没有现在,其实没有所谓的好的状态,只有立刻行动的自己,十八岁和二十八岁看到的风景是不一样的。

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