机器学习的数学基础(上)

news/2024/12/2 15:49:49/

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目录

机器学习的数学基础 1

高等数学 1

线性代数 9

概率论和数理统计 19

机器学习的数学基础 {#机器学习的数学基础 .58}

高等数学

1.导数定义:

导数和微分的概念

f′(x0)=lim⁡Δx→0f(x0+Δx)−f(x0)Δxf'(x_{0}) = \lim_{\Delta x \rightarrow 0}\,\frac{f(x_{0} + \Delta x) - f(x_{0})}{\text{Δx}}f(x0)=limΔx0Δxf(x0+Δx)f(x0)
(1)

或者:f′(x0)=lim⁡x→x0f(x)−f(x0)x−x0f'(x_{0}) = \lim_{x \rightarrow x_{0}}\,\frac{f(x) - f(x_{0})}{x - x_{0}}f(x0)=limxx0xx0f(x)f(x0)
(2)

2.左右导数导数的几何意义和物理意义

函数f(x)f(x)f(x)x0x_{0}x0处的左、右导数分别定义为:

左导数:f′−(x0)=lim⁡Δx→0−f(x0+Δx)−f(x0)Δx=lim⁡x→x0−f(x)−f(x0)x−x0,(x=x0+Δx){f'}_{-}(x_{0}) = \lim_{\Delta x \rightarrow 0^{-}}\,\frac{f(x_{0} + \Delta x) - f(x_{0})}{\text{Δx}} = \lim_{x \rightarrow x_{0}^{-}}\,\frac{f(x) - f(x_{0})}{x - x_{0}},(x = x_{0} + \Delta x)f(x0)=limΔx0Δxf(x0+Δx)f(x0)=limxx0xx0f(x)f(x0),(x=x0+Δx)

右导数:f′+(x0)=lim⁡Δx→0+f(x0+Δx)−f(x0)Δx=lim⁡x→x0+f(x)−f(x0)x−x0{f'}_{+}(x_{0}) = \lim_{\Delta x \rightarrow 0^{+}}\,\frac{f(x_{0} + \Delta x) - f(x_{0})}{\text{Δx}} = \lim_{x \rightarrow x_{0}^{+}}\,\frac{f(x) - f(x_{0})}{x - x_{0}}f+(x0)=limΔx0+Δxf(x0+Δx)f(x0)=limxx0+xx0f(x)f(x0)

3.函数的可导性与连续性之间的关系

Th1:
函数f(x)f(x)f(x)x0x_{0}x0处可微⇔f(x)\Leftrightarrow f(x)f(x)x0x_{0}x0处可导。

**Th2:**若函数在点x0x_{0}x0处可导,则y=f(x)y = f(x)y=f(x)在点x0x_{0}x0处连续,反之则不成立.即函数连续不一定可导。

Th3:f′(x0)f'(x_{0})f(x0)存在⇔f′−(x0)=f′+(x0)\Leftrightarrow {f'}_{-}(x_{0}) = {f'}_{+}(x_{0})f(x0)=f+(x0)

4.平面曲线的切线和法线

切线方程 : y−y0=f′(x0)(x−x0)y - y_{0} = f'(x_{0})(x - x_{0})yy0=f(x0)(xx0)

法线方程:y−y0=−1f′(x0)(x−x0),f′(x0)≠0y - y_{0} = - \frac{1}{f'(x_{0})}(x - x_{0}),f'(x_{0}) \neq 0yy0=f(x0)1(xx0),f(x0)=0

5.四则运算法则

设函数u=u(x),v=v(x)u = u(x),v = v(x)u=u(x),v=v(x)在点xxx可导,则:

(1) (u±v)′=u′±v′\left( u \pm v \right)^{'} = u^{'} \pm v^{'}(u±v)=u±v \text{\ \ \ \ }    

(2) (uv)′=uv′+vu′(\text{uv})' = \text{uv}' + \text{vu}'(uv)=uv+vu
d(uv)=udv+vdud(\text{uv}) = \text{udv} + \text{vdu}d(uv)=udv+vdu

(3) (uv)′=vu′−uv′v2(v≠0)(\frac{u}{v})' = \frac{\text{vu}' - \text{uv}'}{v^{2}}(v \neq 0)(vu)=v2vuuv(v=0)
d(uv)=vdu−udvv2d(\frac{u}{v}) = \frac{\text{vdu} - \text{udv}}{v^{2}}d(vu)=v2vduudv

6.基本导数与微分表

(1) y=cy = cy=c(常数) 则: y′=0y^{'} = 0y=0 dy=0\text{dy} = 0dy=0

(2) y=xαy = x^{\alpha}y=xα(α\alphaα为实数) 则: y′=αxα−1y' = \alpha x^{\alpha - 1}y=αxα1
dy=αxα−1dx\text{dy} = \alpha x^{\alpha - 1}\text{dx}dy=αxα1dx

(3) y=axy = a^{x}y=ax 则: y′=axln⁡ay' = a^{x}\ln ay=axlna dy=axln⁡adx\text{dy} = a^{x}\ln\text{adx}dy=axlnadx
特例: (ex)′=ex(e^{x})' = e^{x}(ex)=ex d(ex)=exdxd(e^{x}) = e^{x}\text{dx}d(ex)=exdx

(4) y′=1xln⁡ay' = \frac{1}{x\ln a}y=xlna1 则:dy=1xln⁡adx\text{dy} = \frac{1}{x\ln a}\text{dx}dy=xlna1dx
特例:y=lnxy = lnxy=lnx (lnx)′=1x(lnx)' = \frac{1}{x}(lnx)=x1 d(lnx)=1xdxd(lnx) = \frac{1}{x}\text{dx}d(lnx)=x1dx

(5) y=sinxy = sinxy=sinx 则:y′=cosxy' = cosxy=cosx d(sinx)=cosxdxd(sinx) = cos\text{xdx}d(sinx)=cosxdx

(6) y=cosxy = cosxy=cosx 则:y′=−sinxy' = - sinxy=sinx d(cosx)=−sinxdxd(cosx) = - sin\text{xdx}d(cosx)=sinxdx

(7) y=tanxy = tanxy=tanx 则: y′=1cos⁡2x=sec⁡2xy^{'} = \frac{1}{\cos^{2}x} = \sec^{2}xy=cos2x1=sec2x
d(tanx)=sec⁡2xdxd(tanx) = \sec^{2}\text{xdx}d(tanx)=sec2xdx

(8) y=cotxy = cotxy=cotx 则:y′=−1sin⁡2x=−csc⁡2xy' = - \frac{1}{\sin^{2}x} = - \csc^{2}xy=sin2x1=csc2x
d(cotx)=−csc⁡2xdxd(cotx) = - \csc^{2}\text{xdx}d(cotx)=csc2xdx

(9) y=secxy = secxy=secx 则:y′=secxtan⁡xy' = secx\tan xy=secxtanx d(secx)=secxtan⁡xdxd(secx) = secx\tan\text{xdx}d(secx)=secxtanxdx

(10) y=cscxy = cscxy=cscx 则:y′=−cscxcot⁡xy' = - cscx\cot xy=cscxcotx d(cscx)=−cscxcot⁡xdxd(cscx) = - cscx\cot\text{xdx}d(cscx)=cscxcotxdx

(11) y=arcsinxy = arcsinxy=arcsinx 则:y′=11−x2y' = \frac{1}{\sqrt{1 - x^{2}}}y=1x21
d(arcsinx)=11−x2dxd(arcsinx) = \frac{1}{\sqrt{1 - x^{2}}}\text{dx}d(arcsinx)=1x21dx

(12) y=arccosxy = arccosxy=arccosx 则:y′=−11−x2y' = - \frac{1}{\sqrt{1 - x^{2}}}y=1x21
d(arccosx)=−11−x2dxd(arccosx) = - \frac{1}{\sqrt{1 - x^{2}}}\text{dx}d(arccosx)=1x21dx

(13) y=arctanxy = arctanxy=arctanx 则:y′=11+x2y' = \frac{1}{1 + x^{2}}y=1+x21
d(arctanx)=11+x2dxd(arctanx) = \frac{1}{1 + x^{2}}\text{dx}d(arctanx)=1+x21dx

(14) y=arccotxy = arccotxy=arccotx 则:y′=−11+x2y' = - \frac{1}{1 + x^{2}}y=1+x21
d(arccotx)=−11+x2dxd(arccotx) = - \frac{1}{1 + x^{2}}\text{dx}d(arccotx)=1+x21dx

(15) y=sxy = sxy=sx 则:y′=cxy' = cxy=cx d(sx)=cxdxd(sx) = cxdxd(sx)=cxdx

(16) y=cxy = cxy=cx 则:y′=sxy' = sxy=sx d(cx)=sxdxd(cx) = sxdxd(cx)=sxdx

7.复合函数,反函数,隐函数以及参数方程所确定的函数的微分法

(1) 反函数的运算法则:
y=f(x)y = f(x)y=f(x)在点xxx的某邻域内单调连续,在点xxx处可导且f′(x)≠0f'(x) \neq 0f(x)=0,则其反函数在点xxx所对应的yyy处可导,并且有dydx=1dxdy\frac{\text{dy}}{\text{dx}} = \frac{1}{\frac{\text{dx}}{\text{dy}}}dxdy=dydx1

(2)
复合函数的运算法则:若μ=φ(x)\mu = \varphi(x)μ=φ(x)在点xxx可导,而y=f(μ)y = f(\mu)y=f(μ)在对应点μ\muμ(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xxx可导,且y′=f′(μ)⋅φ′(x)y' = f'(\mu) \cdot \varphi'(x)y=f(μ)φ(x)

(3) 隐函数导数dydx\frac{\text{dy}}{\text{dx}}dxdy的求法一般有三种方法:

1)方程两边对xxx求导,要记住yyyxxx的函数,则yyy的函数是xxx的复合函数.例如1y\frac{1}{y}y1y2y^{2}y2lny\text{lny}lnyeye^{y}ey等均是xxx的复合函数.
xxx求导应按复合函数连锁法则做。

2)公式法.由F(x,y)=0F(x,y) = 0F(x,y)=0
dydx=−F′x(x,y)F′y(x,y)\frac{\text{dy}}{\text{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)xxxyyy的偏导数。

3)利用微分形式不变性

8.常用高阶导数公式

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(6)莱布尼兹公式:若u(x),v(x)u(x)\,,v(x)u(x),v(x)nnn阶可导,则:
(uv)(n)=∑i=0ncniu(i)v(n−i){(\text{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)=uu^{(0)} = uu(0)=uv(0)=vv^{(0)} = vv(0)=v

9.微分中值定理,泰勒公式

Th1:(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)x0x_{0}x0的某邻域内有定义,并且在此邻域内恒有
f(x)≤f(x0)f(x) \leq f(x_{0})f(x)f(x0)f(x)≥f(x0)f(x) \geq f(x_{0})f(x)f(x0),

(2) f(x)f(x)f(x)x0x_{0}x0处可导,则有 f′(x0)=0f'(x_{0}) = 0f(x0)=0

Th2:(罗尔定理)

设函数f(x)f(x)f(x)满足条件:

(1)在闭区间[a,b]\lbrack a,b\rbrack[a,b]上连续;
(2)在(a,b)(a,b)(a,b)内可导;(3)f(a)=f(b)f\left( a \right) = f\left( b \right)f(a)=f(b)

则在(a,b)(a,b)(a,b)∃\exists一个ξ\xiξ,使 f′(ξ)=0f'(\xi) = 0f(ξ)=0

Th3: (拉格朗日中值定理)

设函数f(x)f(x)f(x)满足条件:

(1)在[a,b]\lbrack a,b\rbrack[a,b]上连续;(2)在(a,b)(a,b)(a,b)内可导;

则在(a,b)(a,b)(a,b)内存在一个ξ\xiξ,使 f(b)−f(a)b−a=f′(ξ)\frac{f(b) - f(a)}{b - a} = f'(\xi)baf(b)f(a)=f(ξ)

Th4: (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) 在[a,b]\lbrack a,b\rbrack[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)≠0g'(x) \neq 0g(x)=0

则在(a,b)(a,b)(a,b)内存在一个ξ\xiξ,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

法则Ⅰ(00\frac{\mathbf{0}}{\mathbf{0}}00型不定式极限)

设函数f(x),g(x)f\left( x \right),g\left( x \right)f(x),g(x)满足条件:
lim⁡x→x0f(x)=0,lim⁡x→x0g(x)=0\lim_{x \rightarrow x_{0}}\, f\left( x \right) = 0,\lim_{x \rightarrow x_{0}}\, g\left( x \right) = 0limxx0f(x)=0,limxx0g(x)=0;
f(x),g(x)f\left( x \right),g\left( x \right)f(x),g(x)x0x_{0}x0的邻域内可导
(在x0x_{0}x0处可除外)且g′(x)≠0g'\left( x \right) \neq 0g(x)=0;

lim⁡x→x0f′(x)g′(x)\lim_{x \rightarrow x_{0}}\,\frac{f'\left( x \right)}{g'\left( x \right)}limxx0g(x)f(x)存在(或∞\infty)。

则:
lim⁡x→x0f(x)g(x)=lim⁡x→x0f′(x)g′(x)\lim_{x \rightarrow x_{0}}\,\frac{f\left( x \right)}{g\left( x \right)} = \lim_{x \rightarrow x_{0}}\,\frac{f'\left( x \right)}{g'\left( x \right)}limxx0g(x)f(x)=limxx0g(x)f(x)

法则I′\mathbf{I'}I
(00\frac{\mathbf{0}}{\mathbf{0}}00型不定式极限)

设函数f(x),g(x)f\left( x \right),g\left( x \right)f(x),g(x)满足条件:
lim⁡x→∞f(x)=0,lim⁡x→∞g(x)=0\lim_{x \rightarrow \infty}\, f\left( x \right) = 0,\lim_{x \rightarrow \infty}\, g\left( x \right) = 0limxf(x)=0,limxg(x)=0;存在一个X>0X > 0X>0,当∣x∣>X\left| x \right| > Xx>X时,f(x),g(x)f\left( x \right),g\left( x \right)f(x),g(x)可导,且g′(x)≠0g'\left( x \right) \neq 0g(x)=0;lim⁡x→x0f′(x)g′(x)\lim_{x \rightarrow x_{0}}\,\frac{f'\left( x \right)}{g'\left( x \right)}limxx0g(x)f(x)存在(或∞\infty)。

则:
lim⁡x→x0f(x)g(x)=lim⁡x→x0f′(x)g′(x).\lim_{x \rightarrow x_{0}}\,\frac{f\left( x \right)}{g\left( x \right)} = \lim_{x \rightarrow x_{0}}\,\frac{f'\left( x \right)}{g'\left( x \right)}.limxx0g(x)f(x)=limxx0g(x)f(x).

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

设函数f(x),g(x)f\left( x \right),g\left( x \right)f(x),g(x)满足条件:
lim⁡x→x0f(x)=∞,lim⁡x→x0g(x)=∞\lim_{x \rightarrow x_{0}}\, f\left( x \right) = \infty,\lim_{x \rightarrow x_{0}}\, g\left( x \right) = \inftylimxx0f(x)=,limxx0g(x)=;
f(x),g(x)f\left( x \right),g\left( x \right)f(x),g(x)x0x_{0}x0 的邻域内可
导(在x0x_{0}x0处可除外)且g′(x)≠0g'\left( x \right) \neq 0g(x)=0;lim⁡x→x0f′(x)g′(x)\lim_{x \rightarrow x_{0}}\,\frac{f'\left( x \right)}{g'\left( x \right)}limxx0g(x)f(x)存在(或∞\infty)。

则:
lim⁡x→x0f(x)g(x)=lim⁡x→x0f′(x)g′(x).\lim_{x \rightarrow x_{0}}\,\frac{f\left( x \right)}{g\left( x \right)} = \lim_{x \rightarrow x_{0}}\,\frac{f'\left( x \right)}{g'\left( x \right)}.limxx0g(x)f(x)=limxx0g(x)f(x).

同理法则II′II'II(∞∞\frac{\infty}{\infty}型不定式极限)仿法则I′I'I可写出

11.泰勒公式

设函数f(x)f(x)f(x)在点x0x_{0}x0处的某邻域内具有n+1n + 1n+1阶导数,则对该邻域内异于x0x_{0}x0的任意点xxx,在x0x_{0}x0xxx之间至少存在一个ξ\xiξ,使得:

f(x)=f(x0)+f′(x0)(x−x0)+12!f′′(x0)(x−x0)2+⋯f(x) = f(x_{0}) + f'(x_{0})(x - x_{0}) + \frac{1}{2!}f''(x_{0}){(x - x_{0})}^{2} + \cdotsf(x)=f(x0)+f(x0)(xx0)+2!1f′′(x0)(xx0)2+
+f(n)(x0)n!(x−x0)n+Rn(x)+ \frac{f^{(n)}(x_{0})}{n!}{(x - x_{0})}^{n} + R_{n}(x)+n!f(n)(x0)(xx0)n+Rn(x)

其中
Rn(x)=f(n+1)(ξ)(n+1)!(x−x0)n+1R_{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x0x_{0}x0处的nnn阶泰勒余项。

x0=0x_{0} = 0x0=0,则nnn阶泰勒公式:

f(x)=f(0)+f′(0)x+12!f′′(0)x2+⋯+f(n)(0)n!xn+Rn(x)f(x) = f(0) + f'(0)x + \frac{1}{2!}f''(0)x^{2} + \cdots + \frac{f^{(n)}(0)}{n!}x^{n} + R_{n}(x)f(x)=f(0)+f(0)x+2!1f′′(0)x2++n!f(n)(0)xn+Rn(x)……

(1) 其中
Rn(x)=f(n+1)(ξ)(n+1)!xn+1R_{n}(x) = \frac{f^{(n + 1)}(\xi)}{(n + 1)!}x^{n + 1}Rn(x)=(n+1)!f(n+1)(ξ)xn+1ξ\xiξ在0与xxx之间。(1)式称为麦克劳林公式

常用五种函数在x0=0x_{0} = 0x0=0处的泰勒公式 :

ex=1+x+12!x2+⋯+1n!xn+xn+1(n+1)!eξe^{x} = 1 + x + \frac{1}{2!}x^{2} + \cdots + \frac{1}{n!}x^{n} + \frac{x^{n + 1}}{(n + 1)!}e^{\xi}ex=1+x+2!1x2++n!1xn+(n+1)!xn+1eξ
=1+x+12!x2+⋯+1n!xn+o(xn)= 1 + x + \frac{1}{2!}x^{2} + \cdots + \frac{1}{n!}x^{n} + o(x^{n})=1+x+2!1x2++n!1xn+o(xn)

sin⁡x=x−13!x3+⋯+xnn!sin⁡nπ2+xn+1(n+1)!sin⁡(ξ+n+12π)\sin x = x - \frac{1}{3!}x^{3} + \cdots + \frac{x^{n}}{n!}\sin\frac{\text{nπ}}{2} + \frac{x^{n + 1}}{\left( n + 1 \right)!}\sin\left( \xi + \frac{n + 1}{2}\pi \right)sinx=x3!1x3++n!xnsin2+(n+1)!xn+1sin(ξ+2n+1π)


=x−13!x3+⋯+xnn!sin⁡nπ2+o(xn)= x - \frac{1}{3!}x^{3} + \cdots + \frac{x^{n}}{n!}\sin\frac{\text{nπ}}{2} + o\left( x^{n} \right)=x3!1x3++n!xnsin2+o(xn)

cos⁡x=1−12!x2+⋯+xnn!cos⁡nπ2+xn+1(n+1)!cos(ξ+n+12π)\cos x = 1 - \frac{1}{2!}x^{2} + \cdots + \frac{x^{n}}{n!}\cos\frac{\text{nπ}}{2} + \frac{x^{n + 1}}{(n + 1)!}cos(\xi + \frac{n + 1}{2}\pi)cosx=12!1x2++n!xncos2+(n+1)!xn+1cos(ξ+2n+1π)


=1−12!x2+⋯+xnn!cos⁡nπ2+o(xn)= 1 - \frac{1}{2!}x^{2} + \cdots + \frac{x^{n}}{n!}\cos\frac{\text{nπ}}{2} + o(x^{n})=12!1x2++n!xncos2+o(xn)

ln(1+x)=x−12x2+13x3−⋯+(−1)n−1xnn+(−1)nxn+1(n+1)(1+ξ)n+1ln(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


=x−12x2+13x3−⋯+(−1)n−1xnn+o(xn)= x - \frac{1}{2}x^{2} + \frac{1}{3}x^{3} - \cdots + {( - 1)}^{n - 1}\frac{x^{n}}{n} + o(x^{n})=x21x2+31x3+(1)n1nxn+o(xn)

(1+x)m=1+mx+m(m−1)2!x2+⋯+m(m−1)⋯(m−n+1)n!xn{(1 + x)}^{m} = 1 + \text{mx} + \frac{m(m - 1)}{2!}x^{2} + \cdots + \frac{m(m - 1)\cdots(m - n + 1)}{n!}x^{n}(1+x)m=1+mx+2!m(m1)x2++n!m(m1)(mn+1)xn
+m(m−1)⋯(m−n+1)(n+1)!xn+1(1+ξ)m−n−1+ \frac{m(m - 1)\cdots(m - n + 1)}{(n + 1)!}x^{n + 1}{(1 + \xi)}^{m - n - 1}+(n+1)!m(m1)(mn+1)xn+1(1+ξ)mn1


(1+x)m=1+mx+m(m−1)2!x2+⋯+m(m−1)⋯(m−n+1)n!xn+o(xn){(1 + x)}^{m} = 1 + \text{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

Th1:
设函数f(x)f(x)f(x)(a,b)(a,b)(a,b)区间内可导,如果对∀x∈(a,b)\forall x \in (a,b)x(a,b),都有KaTeX parse error: Got group of unknown type: 'internal'(或KaTeX parse error: Got group of unknown type: 'internal'),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)。

Th2:
(取极值的必要条件)设函数f(x)f(x)f(x)x0x_{0}x0处可导,且在x0x_{0}x0处取极值,则KaTeX parse error: Got group of unknown type: 'internal'.

Th3:
(取极值的第一充分条件)设函数f(x)f(x)f(x)x0x_{0}x0的某一邻域内可微,且KaTeX parse error: Got group of unknown type: 'internal'(或f(x)f(x)f(x)x0x_{0}x0处连续,但KaTeX parse error: Got group of unknown type: 'internal'不存在.)。

(1)若当xxx经过x0x_{0}x0时,KaTeX parse error: Got group of unknown type: 'internal'由“+”变“-”,则f(x0)f(x_{0})f(x0)为极大值;

(2)若当xxx经过x0x_{0}x0时,KaTeX parse error: Got group of unknown type: 'internal'由“-”变“+”,则f(x0)f(x_{0})f(x0)为极小值;

(3)若KaTeX parse error: Got group of unknown type: 'internal'经过x=x0x = x_{0}x=x0的两侧不变号,则f(x0)f(x_{0})f(x0)不是极值。

Th4:
(取极值的第二充分条件)设f(x)f(x)f(x)在点x0x_{0}x0处有f′′(x)≠0f''(x) \neq 0f′′(x)=0,且KaTeX parse error: Got group of unknown type: 'internal',则:

KaTeX parse error: Got group of unknown type: 'internal'时,f(x0)f(x_{0})f(x0)为极大值;
KaTeX parse error: Got group of unknown type: 'internal'时,f(x0)f(x_{0})f(x0)为极小值.
注:如果KaTeX parse error: Got group of unknown type: 'internal',此方法失效。

13.渐近线的求法

(1)水平渐近线

lim⁡x→+∞f(x)=b\lim_{x \rightarrow + \infty}\, f(x) = blimx+f(x)=b,或lim⁡x→−∞f(x)=b\lim_{x \rightarrow - \infty}\, f(x) = blimxf(x)=b,则y=by = by=b
称为函数y=f(x)y = f(x)y=f(x)的水平渐近线。

(2)铅直渐近线

lim⁡x→x0−f(x)=∞\lim_{x \rightarrow x_{0}^{-}}\, f(x) = \inftylimxx0f(x)=,或lim⁡x→x0+f(x)=∞\lim_{x \rightarrow x_{0}^{+}}\, f(x) = \inftylimxx0+f(x)=,则x=x0x = x_{0}x=x0
称为y=f(x)y = f(x)y=f(x)的铅直渐近线。

(3)斜渐近线
a=lim⁡x→∞f(x)x,b=lim⁡x→∞[f(x)−ax]a = \lim_{x \rightarrow \infty}\,\frac{f(x)}{x},\quad b = \lim_{x \rightarrow \infty}\,\lbrack f(x) - \text{ax}\rbracka=limxxf(x),b=limx[f(x)ax],则
y=ax+by = \text{ax} + by=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

Th1: (凹凸性的判别定理)若在I上f′′(x)<0f''(x) < 0f′′(x)<0(或f′′(x)>0f''(x) > 0f′′(x)>0),
f(x)f(x)f(x)在I上是凸的(或凹的)。

Th2:
(拐点的判别定理1)若在x0x_{0}x0f′′(x)=0f''(x) = 0f′′(x)=0,(或f′′(x)f''(x)f′′(x)不存在),当xxx变动经过x0x_{0}x0时,f′′(x)f''(x)f′′(x)变号,则(x0,f(x0))(x_{0},f(x_{0}))(x0,f(x0))为拐点。

Th3:
(拐点的判别定理2)设f(x)f(x)f(x)x0x_{0}x0点的某邻域内有三阶导数,且f′′(x)=0f''(x) = 0f′′(x)=0f′′′(x)≠0f'''(x) \neq 0f′′′(x)=0,则(x0,f(x0))(x_{0},f(x_{0}))(x0,f(x0))为拐点。

15.弧微分

dS=1+y′2dx\text{dS} = \sqrt{1 + y'^{2}}\text{dx}dS=1+y2dx

16.曲率

曲线y=f(x)y = f(x)y=f(x)在点(x,y)(x,y)(x,y)处的曲率k=∣y′′∣(1+y′2)32.k = \frac{\left| y'' \right|}{{(1 + y'^{2})}^{\frac{3}{2}}}.k=(1+y2)23y′′.
对于参数方程:

{x=φ(t)y=ψ(t),k=∣φ′(t)ψ′′(t)−φ′′(t)ψ′(t)∣[φ′2(t)+ψ′2(t)]32\left\{ \begin{matrix} & x = \varphi(t) \\ & y = \psi(t) \\ \end{matrix} \right.\ ,k = \frac{\left| \varphi'(t)\psi''(t) - \varphi''(t)\psi'(t) \right|}{{\lbrack\varphi'^{2}(t) + \psi'^{2}(t)\rbrack}^{\frac{3}{2}}}{x=φ(t)y=ψ(t) ,k=[φ2(t)+ψ2(t)]23φ(t)ψ′′(t)φ′′(t)ψ(t)

17.曲率半径

曲线在点MMM处的曲率k(k≠0)k(k \neq 0)k(k=0)与曲线在点MMM处的曲率半径ρ\rhoρ有如下关系:ρ=1k\rho = \frac{1}{k}ρ=k1

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