--- author: Alvie Rahman date: \today title: MMME1026 // Calculus tags: - uni - nottingham - mechanical - engineering - mmme1026 - maths - calculus uuid: 126b21f8-e188-48f6-9151-5407f2b2b644 --- # Calculus of One Variable Functions ## Key Terms
### Function A function is a rule that assigns a **unique** value $f(x)$ to each value $x$ in a given *domain*. The set of value taken by $f(x)$ when $x$ takes all possible value in the domain is the *range* of $f(x)$.
### Rational Functions A function of the type $$ \frac{f(x)}{g(x)} $$ where $f$ and $g$ are polynomials, is called a rational function. Its range has to exclude all those values of $x$ where $g(x) = 0$.
### Inverse Functions Consider the function $f(x) = y$. If $f$ is such that for each $y$ in the range there is exactly one $x$ in the domain, we can define the inverse $f^{-1}$ as: $$f^{-1}(y) = f^{-1}(f(x)) = x$$
### Limits Consider the following: $$f(x) = \frac{\sin x}{x}$$ The value of the function can be easily calculated when $x \neq 0$, but when $x=0$, we get the expression $\frac{\sin 0 }{0}$. However, when we evaluate $f(x)$ for values that approach 0, those values of $f(x)$ approach 1. This suggests defining the limit of a function $$\lim_{x \rightarrow a} f(x)$$ to be the limiting value, if it exists, of $f(x)$ as $x$ gets approaches $a$. #### Limits from Above and Below Sometimes approaching 0 with small positive values of $x$ gives you a different limit from approaching with small negative values of $x$. The limit you get from approaching 0 with positive values is known as the limit from above: $$\lim_{x \rightarrow a^+} f(x)$$ and with negative values is known as the limit from below: $$\lim_{x \rightarrow a^-} f(x)$$ If the two limits are equal, we simply refer to the *limit*.
## Important Functions
### Exponential Functions $$f(x) = e^x = \exp x$$ It can also be written as an infinite series: $$\exp x = e^x = 1 + x + \frac{x^2}{2!} + \frac{x^3}{3!} + ...$$ The two important limits to know are: - as $x \rightarrow + \infty$, $\exp x \rightarrow +\infty$ ($e^x \rightarrow +\infty$) - as $x \rightarrow -\infty$, $\exp x \rightarrow 0$ ($e^x \rightarrow 0$) Note that $e^x > 0$ for all real values of $x$.
### Hyperbolic Functions (sinh and cosh) The hyperbolic sine ($\sinh$) and hyperbolic cosine function ($\cosh$) are defined by: $$\sinh x = \frac 1 2 (e^x - e^{-x}) \text{ and } \cosh x = \frac 1 2 (e^x + e^{-x})$$ $$\tanh = \frac{\sinh x}{\cosh x}$$ ![[Fylwind at English Wikipedia, Public domain, via Wikimedia Commons](https://commons.wikimedia.org/wiki/File:Sinh_cosh_tanh.svg)](./images/Sinh_cosh_tanh.svg) Some key facts about these functions: - $\cosh$ has even symmetry and $\sinh$ and $\tanh$ have odd symmetry - as $x \rightarrow + \infty$, $\cosh x \rightarrow +\infty$ and $\sinh x \rightarrow +\infty$ - $\cosh^2x - \sinh^2x = 1$ - $\tanh$'s limits are -1 and +1 - Derivatives: - $\frac{\mathrm{d}}{\mathrm{d}x} \sinh x = \cosh x$ - $\frac{\mathrm{d}}{\mathrm{d}x} \cosh x = \sinh x$ - $\frac{\mathrm{d}}{\mathrm{d}x} \tanh x = \frac{1}{\cosh^2x}$
### Natural Logarithm $$\ln{e^y} = \ln{\exp y} = y$$ Since the exponential of any real number is positive, the domain of $\ln$ is $x > 0$.
### Implicit Functions An implicit function takes the form $$f(x, y) = 0$$ To draw the curve of an implicit function you have to rewrite it in the form $y = f(x)$. There may be more than one $y$ value for each $x$ value.
# Differentiation The derivative of the function $f(x)$ is denoted by: $$f'(x) \text{ or } \frac{\mathrm{d}}{\mathrm dx} f(x)$$ Geometrically, the derivative is the gradient of the curve $y = f(x)$. It is a measure of the rate of change of $f(x)$ as $x$ varies. For example, velocity, $v$, is the rate of change of displacement, $s$, with respect to time, $t$, or: $$v = \frac{\mathrm ds}{dt}$$
#### Formal Definition ![](./images/vimscrot-2021-12-27T14:33:20,836330991+00:00.png) As $h\rightarrow 0$, the clospe of the cord $\rightarrow$ slope of the tangent, or: $$f'(x_0) = \lim_{h\rightarrow0}\frac{f(x_0+h) - f(x_0)}{h}$$ whenever this limit exists.
## Rules for Differentiation ### Powers $$\frac{\mathrm d}{\mathrm dx} x^n = nx^{-1}$$ ### Trigonometric Functions $$\frac{\mathrm d}{\mathrm dx} \sin x = \cos x$$ $$\frac{\mathrm d}{\mathrm dx} \cos x = \sin x$$ ### Exponential Functions $$\frac{\mathrm d}{\mathrm dx} e^{kx} = ke^{kx}$$ $$\frac{\mathrm d}{\mathrm dx} \ln kx^n = \frac n x$$ where $n$ and $k$ are constant. ### Linearity $$\frac{\mathrm d}{\mathrm dx} (f + g) = \frac{\mathrm d}{\mathrm dx} f + \frac{\mathrm d}{\mathrm dx} g$$ ### Product Rule $$\frac{\mathrm d}{\mathrm dx} (fg) = \frac{\mathrm df}{\mathrm dx}g + \frac{\mathrm dg}{\mathrm dx}f$$ ### Quotient Rule $$ \frac{\mathrm d}{\mathrm dx} \frac f g = \frac 1 {g^2} \left( \frac{\mathrm df}{\mathrm dx} g - f \frac{\mathrm dg}{\mathrm dx} \right) $$ $$ \left( \frac f g \right)' = \frac 1 {g^2} (gf' - fg')$$ ### Chain Rule Let $$f(x) = F(u(x))$$ $$ \frac{\mathrm df}{\mathrm dx} = \frac{\mathrm{d}F}{\mathrm du} \frac{\mathrm du}{\mathrm dx} $$
#### Example 1 Differentiate $f(x) = \cos{x^2}$. Let $u(x) = x^2$, $F(u) = \cos u$ $$ \frac{\mathrm df}{\mathrm dx} = -\sin u \cdot 2x = 2x\sin{x^2} $$
## L'Hôpital's Rule l'Hôpital's rule provides a systematic way of dealing with limits of functions like $\frac{\sin x} x$. Suppose $$\lim_{x\rightarrow{a}} f(x) = 0$$ and $$\lim_{x\rightarrow{a}} g(x) = 0$$ and we want $\lim_{x\rightarrow{a}} \frac{f(x)}{g(x)}$. If $$\lim_{x\rightarrow{a}} \frac{f'(x)}{g'(x)} = L $$ where any $L$ is any real number or $\pm \infty$, then $$\lim_{x\rightarrow{a}} \frac{f(x)}{g(x)} = L$$ You can keep applying the rule until you get a sensible answer. # Graphs ## Stationary Points An important application of calculus is to find where a function is a maximum or minimum. ![](./images/vimscrot-2021-12-27T15:30:26,494800477+00:00.png) when these occur the gradient of the tangent to the curve, $f'(x) = 0$. The condition $f'(x) = 0$ alone however does not guarantee a minimum or maximum. It only means that point is a *stationary point*. There are three main types of stationary points: - maximum - minimum - point of inflection ### Local Maximum The point $x = a$ is a local maximum if: $$f'(a) = 0 \text{ and } f''(a) < 0$$ This is because $f'(x)$ is a decreasing function of $x$ near $x=a$. ### Local Minimum The point $x = a$ is a local minimum if: $$f'(a) = 0 \text{ and } f''(a) > 0$$ This is because $f'(x)$ is a increasing function of $x$ near $x=a$. ### Point of Inflection $$f'(a) = 0 \text{ and } f''(a) = 0 \text { and } f'''(a) \ne 0$$ #### $f'''(a) > 0$ ![](./images/vimscrot-2021-12-27T15:38:11,125781274+00:00.png) #### $f'''(a) < 0$ ![](./images/vimscrot-2021-12-27T15:38:29,395666506+00:00.png) # Approximating with the Taylor series The expansion $$e^x = 1 + x + \frac{x^2}{2!} + \frac{x^3}{3!} + \cdots$$ is an example of a *Taylor series*. These enable us to approximate a given function f(x) using a series which is often easier to calculate. Among other uses, they help us: - calculate complicated function using simple arithmetic operations - find useful analytical approximations which work for $x$ near a given value (e.g. $e^x \approx 1 + x$ for $x$ near 0) - Understand the behaviour of a function near a stationary point ## Strategy Suppose we know information about $f(x)$ only at the point $x=0$. How can we find out about $f$ for other values of $x$? We could approximate the function by successive polynomials, each time matching more derivatives at $x=0$. \begin{align*} g(x) = a_0 &\text{ using } f(0) \\ g(x) = a_0 + a_1x &\text{ using } f(0), f'(0) \\ g(x) = a_0 + a_1x + a_2x^2 &\text{ using } f(0), f'(0), f''(0) \\ &\text{and so on...} \end{align*}
#### Example 1 For $x$ near 0, approximate $f(x) = \cos x$ by a quadratic. 1. Set $f(0) = g(0$: $$f(0) = 1 \rightarrow g(0) = a_0 = 1$$ 2. Set $f'(0) = g'(0$: $$f'(0) = -\sin0 = 0 \rightarrow g'(0) = a_1 = 0$$ 3. Set $f''(0) = g''(0$: $$f''(0) = -\cos = -1 \rightarrow g''(0) = 2a_2 = -1 \rightarrow a_2 = -0.5$$ So for $x$ near 0, $$\cos x \approx 1 - \frac 1 2 x^2$$ Check: $x$ | $\cos x$ | $1 - 0.5x^2$ --- | -------- | ------------ 0.4 | 0.921061 | 0.920 0.2 | 0.960066 | 0.980 0.1 | 0.995004 | 0.995
## General Case ### Maclaurin Series A Maclaurin series is a Taylor series expansion of a function about 0. Any function $f(x)$ can be written as an infinite *Maclaurin Series* $$f(x) = a_0 + a_1x + a_2x^2 + a_3x^2 + \cdots$$ where $$a_0 = f(0) \qquad a_n = \frac 1 {n!} \frac{\mathrm d^nf}{\mathrm dx^n} \bigg|_{x=0}$$ ($|_{x=0}$ means evaluated at $x=0$) ### Taylor Series We may alternatively expand about any point $x=a$ to give a Taylor series: \begin{align*} f(x) = &f(a) + (x-a)f'(a) \\ & + \frac 1 {2!}(x-a)^2f''(a) \\ & + \frac 1 {3!}(x-a)^3f'''(a) \\ & + \cdots + \frac 1 {n!}(x-a)^nf^{(n)}(a) \end{align*} a generalisation of a Maclaurin series. An alternative form of Taylor series is given by setting $x = a+h$ where $h$ is small: $$f(a+h) = f(a) + hf'(a) + \cdots + \frac 1 {n!}h^nf^{(n)}(a) + \cdots$$ ## Taylor Series at a Stationary Point If f(x) has a stationary point at $x=a$, then $f'(a) = 0$ and the Taylor series begins $$f(x) = f(a) + \frac 1 2 f''(a)(x-a)^2 + \cdots$$ - If $f''(a) > 0$ then the quadratic part makes the function increase going away from $x=a$ and we have a minimum - If $f''(a) < 0$ then the quadratic part makes the function decrease going away from $x=a$ and we have a maximum - If $f''(a) = 0$ then we must include a higer order terms to determine what happens have a minimum # Integration Integration is the reverse of [differentiation](#differentiation). Take velocity and displacement as an example: $$\int\! v \mathrm dt = s + c$$ where $c$ is the constant of integration, which is required for [indefinite integrals](#indefinite-integrals).A ## Definite Integrals The definite integral of a function $f(x)$ in the range $a \le x \le b$ is denoted be: $$\int^b_a \! f(x) \,\mathrm dx$$ If $f(x) = F'(x)$ ($f(x)$ is the derivative of $F(x)$) then $$\int^b_a \! f(x) \,\mathrm dx = \left[F(x)\right]^b_a = F(b) - F(a)$$ ## Area and Integration Approximate the area under a smooth curve using a large number of narrow rectangles. ![](./images/vimscrot-2021-12-28T15:18:59,911868873+00:00.png) Area under curve $\approx \sum_{n} f(x_n)\Delta x_n$. As the rectangles get more numerous and narrow, the approximation approaches the real area. The limiting value is denoted $$\approx \sum_{n} f(x_n)\Delta x_n \rightarrow \int^b_a\! f(x) \mathrm dx$$ This explains the notation used for integrals.
#### Example 1 Calculate the area between these two curves: \begin{align*} y &= f_1(x) = 2 - x^2 \\ y &= f_2(x) = x \end{align*} ![](./images/vimscrot-2021-12-28T15:25:12,556743251+00:00.png) 1. Find the crossing points $P$ and $Q$ \begin{align*} f_1(x) &= f_2(x) \\ x &= 2-x^2 \\ x &= 1 \\ x &= -2 \end{align*} 2. Since $f_1(x) \ge f_2(x)$ between $P$ and $Q$ \begin{align*} A &= \int^1_{-2}\! (f_1(x) - f_2(x)) \mathrm dx \\ &= \int^1_{-2}\! (2 - x^2 - x) \mathrm dx \\ &= \left[ 2x - \frac 13 x^3 - \frac 12 x^2 \right]^1_{-2} \\ &= \left(2 - \frac 13 - \frac 12 \right) - \left( -4 + \frac 83 - \frac 42 \right) \\ &= \frac 92 \end{align*}
## Techniques for Integration Integration requires multiple techniques and methods to do correctly because it is a PITA. These are best explained by examples so try to follow those rather than expect and explanation. ### Integration by Substitution Integration but substitution lets us integrate functions of functions.
#### Example 1 Find $$I = \int\!(5x - 1)^3 \mathrm dx$$ 1. Let $w(x) = 5x - 1$ 2. \begin{align*} \frac{\mathrm d}{\mathrm dx} w &= 5 \\ \frac 15 \mathrm dw &= \mathrm dx \end{align*} 3. The integral is then \begin{align*} I &= \int\! w^3 \frac 15 \mathrm dw \\ &= \frac 15 \cdot \frac 14 \cdot w^4 + c \\ &= \frac{1}{20}w^4 + c \end{align*} 4. Finally substitute $w$ out $$I = \frac{(5x-1)^4}{20} + c$$
#### Example 2 Find $$I = \int\! \cos x \sqrt{\sin x + 1} \mathrm dx$$ 1. Let $$w(x) = \sin x + 1$$ 2. Then \begin{align*} \frac{\mathrm d}{\mathrm dx} w = \cos x \\ \mathrm dw = \cos x \mathrm dx \\ \end{align*} 3. The integral is now \begin{align*} I &= \int\! \sqrt w \,\mathrm dw \\ &= \int\! w^{\frac12} \,\mathrm dw \\ &= \frac23w^{\frac32} + c \end{align*} 4. Finally substitute $w$ out to get: $$I = \frac23 (\sin x + 1)^{\frac32} + c$$
#### Example 3 Find $$I = \int^{\frac\pi2}_0\! \cos x \sqrt{\sin x + 1} \,\mathrm dx$$ 1. Use the previous example to get to $$I = \int^2_1\! \sqrt w \,\mathrm dw = \frac23w^{\frac32} + c$$ 2. Since $w(x) = \sin x + 1$ the limits are: \begin{align*} x = 0 &\rightarrow w = 1\\ x = \frac\pi2 &\rightarrow w = 2 \end{align*} 3. This gives us $$I = \left[ \frac23w^{\frac32} \right]^2_1 = \frac23 (2^{\frac23} = 1)$$
#### Example 4 Find $$I = \int^1_0\! \sqrt{1 - x^2} \,\mathrm dx$$ 1. Try a trigonmetrical substitution: \begin{align*} x &= \sin w \\ \\ \frac{\mathrm dx}{\mathrm dw} = \cos w \\ \mathrm dx = \cos 2 \,\mathrm dw \\ \end{align*} 2. \begin{align*} x=0 &\rightarrow w=0 \\ x=1 &\rightarrow w=\frac\pi2 \end{align*} 3. Therefore \begin{align*} I &= \int^{\frac\pi2}_0\! \sqrt{1 - \sin^2 w} \cos w \,\mathrm dw \\ &= \int^{\frac\pi2}_0\! \cos^w w \,\mathrm dw \end{align*} But $\cos(2w) = 2\cos^2w - 1$ so: $$\cos^2w = \frac12 \cos(2w) + \frac12$$ Hence \begin{align*} I &= \int^{\frac\pi2}_0\! \frac12 \cos(2w) + \frac12 \,\mathrm dw \\ &= \left[ \frac14 \sin(2w) + \frac w2 \right]^{\frac\pi2}_0 \\ &= \left( \frac14 \sin\pi + \frac\pi4 \right) - 0 \\ &= \frac\pi4 \end{align*} ### Integration by Parts $$uv = \int\! u\frac{\mathrm dv}{\mathrm dx} \,\mathrm dx + \int\! \frac{\mathrm du}{\mathrm dx}v \,\mathrm dx$$ or $$\int\! u\frac{\mathrm dv}{\mathrm dx} \,\mathrm dx = uv - \int\! \frac{\mathrm du}{\mathrm dx}v \,\mathrm dx$$ This technique is derived from integrating the product rule.
#### Example 1 Find $$I = \int\! \ln x \,\mathrm dx$$ 1. Use $$\int\! u\frac{\mathrm dv}{\mathrm dx} \,\mathrm dx = uv - \int\! \frac{\mathrm du}{\mathrm dx}v \,\mathrm dx$$ 2. Set $u = \ln x$ and $v' = 1$. 3. This means that $u' = \frac1x$ and $v = x$. 4. \begin{align*} I &= x\ln x - \int\! x\cdot\frac1x \,\mathrm dx + c \\ &= x\ln x - \int\! \,\mathrm dx + c \\ &= x\ln x - x + c \\ \end{align*}
# Application of Integration ## Differential Equations Consider the equation $$\frac{\mathrm dy}{\mathrm dx} = y^2$$ To find $y$, is not a straightforward integration: $$y = \int\!y^2 \,\mathrm dx$$ The equation above does not solve for $y$ as we can't integrate the right until we know $y$... which is what we're trying to find. This is an example of a first order differential equation. The general form is: $$\frac{\mathrm dy}{\mathrm dx} = F(x, y)$$ ### Separable Differential Equations A first order diferential equation is called *separable* if it is of the form $$\frac{\mathrm dy}{\mathrm dx} = f(x)g(y)$$ We can solve these by rearranging: $$\frac1{g(y} \cdot \frac{\mathrm dy}{\mathrm dx} = f(x)$$ $$\int\! \frac1{g(y)} \,\mathrm dy = \int\! f(x) \,\mathrm dx + c$$
#### Example 1 Find $y$ such that $$\frac{\mathrm dy}{\mathrm dx} = ky$$ where $k$ is a constant. Rearrange to get \begin{align*} \int\! \frac1y \,\mathrm dy &= \int\! k \mathrm dx + c \\ \ln y &= kx + c \\ y &= e^{kx + c} = e^ce^{kx} \\ &= Ae^{kx} \end{align*} where $A = e^c$ is an arbitrary constant.