title: MMME1026 // Calculus

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Calculus of One Variable Functions

Key Terms

Function

A function is a rule that assigns a unique value f(x)f(x) to each value xx in a given domain.

The set of value taken by f(x)f(x) when xx takes all possible value in the domain is the range of f(x)f(x).

Rational Functions

A function of the type

f(x)g(x) \frac{f(x)}{g(x)}

where ff and gg are polynomials, is called a rational function.

Its range has to exclude all those values of xx where g(x)=0g(x) = 0.

Inverse Functions

Consider the function f(x)=yf(x) = y. If ff is such that for each yy in the range there is exactly one xx in the domain, we can define the inverse f1f^{-1} as:

f1(y)=f1(f(x))=xf^{-1}(y) = f^{-1}(f(x)) = x

Limits

Consider the following:

f(x)=sinxxf(x) = \frac{\sin x}{x}

The value of the function can be easily calculated when x0x \neq 0, but when x=0x=0, we get the expression sin00\frac{\sin 0 }{0}. However, when we evaluate f(x)f(x) for values that approach 0, those values of f(x)f(x) approach 1.

This suggests defining the limit of a function

limxaf(x)\lim_{x \rightarrow a} f(x)

to be the limiting value, if it exists, of f(x)f(x) as xx gets approaches aa.

Limits from Above and Below

Sometimes approaching 0 with small positive values of xx gives you a different limit from approaching with small negative values of xx.

The limit you get from approaching 0 with positive values is known as the limit from above:

limxa+f(x)\lim_{x \rightarrow a^+} f(x)

and with negative values is known as the limit from below:

limxaf(x)\lim_{x \rightarrow a^-} f(x)

If the two limits are equal, we simply refer to the limit.

Important Functions

Exponential Functions

f(x)=ex=expxf(x) = e^x = \exp x

It can also be written as an infinite series:

expx=ex=1+x+x22!+x33!+...\exp x = e^x = 1 + x + \frac{x^2}{2!} + \frac{x^3}{3!} + ...

The two important limits to know are:

Note that ex>0e^x > 0 for all real values of xx.

Hyperbolic Functions (sinh and cosh)

The hyperbolic sine (sinh\sinh) and hyperbolic cosine function (cosh\cosh) are defined by:

sinhx=12(exex) and coshx=12(ex+ex)\sinh x = \frac 1 2 (e^x - e^{-x}) \text{ and } \cosh x = \frac 1 2 (e^x + e^{-x}) tanh=sinhxcoshx\tanh = \frac{\sinh x}{\cosh x}

Fylwind at English Wikipedia, Public domain, via Wikimedia Commons

Some key facts about these functions:

Natural Logarithm

lney=lnexpy=y\ln{e^y} = \ln{\exp y} = y

Since the exponential of any real number is positive, the domain of ln\ln is x>0x > 0.

Implicit Functions

An implicit function takes the form

f(x,y)=0f(x, y) = 0

To draw the curve of an implicit function you have to rewrite it in the form y=f(x)y = f(x). There may be more than one yy value for each xx value.

Differentiation

The derivative of the function f(x)f(x) is denoted by:

f(x) or ddxf(x)f'(x) \text{ or } \frac{\mathrm{d}}{\mathrm dx} f(x)

Geometrically, the derivative is the gradient of the curve y=f(x)y = f(x).

It is a measure of the rate of change of f(x)f(x) as xx varies.

For example, velocity, vv, is the rate of change of displacement, ss, with respect to time, tt, or:

v=dsdtv = \frac{\mathrm ds}{dt}

Formal Definition

As h0h\rightarrow 0, the clospe of the cord \rightarrow slope of the tangent, or:

f(x0)=limh0f(x0+h)f(x0)hf'(x_0) = \lim_{h\rightarrow0}\frac{f(x_0+h) - f(x_0)}{h}

whenever this limit exists.

Rules for Differentiation

Powers

ddxxn=nx1\frac{\mathrm d}{\mathrm dx} x^n = nx^{-1}

Trigonometric Functions

ddxsinx=cosx\frac{\mathrm d}{\mathrm dx} \sin x = \cos x ddxcosx=sinx\frac{\mathrm d}{\mathrm dx} \cos x = \sin x

Exponential Functions

ddxekx=kekx\frac{\mathrm d}{\mathrm dx} e^{kx} = ke^{kx}

ddxlnkxn=nx\frac{\mathrm d}{\mathrm dx} \ln kx^n = \frac n x

where nn and kk are constant.

Linearity

ddx(f+g)=ddxf+ddxg\frac{\mathrm d}{\mathrm dx} (f + g) = \frac{\mathrm d}{\mathrm dx} f + \frac{\mathrm d}{\mathrm dx} g

Product Rule

ddx(fg)=dfdxg+dgdxf\frac{\mathrm d}{\mathrm dx} (fg) = \frac{\mathrm df}{\mathrm dx}g + \frac{\mathrm dg}{\mathrm dx}f

Quotient Rule

ddxfg=1g2(dfdxgfdgdx) \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)

(fg)=1g2(gffg) \left( \frac f g \right)' = \frac 1 {g^2} (gf' - fg')

Chain Rule

Let

f(x)=F(u(x))f(x) = F(u(x))

dfdx=dFdududx \frac{\mathrm df}{\mathrm dx} = \frac{\mathrm{d}F}{\mathrm du} \frac{\mathrm du}{\mathrm dx}

Example 1

Differentiate f(x)=cosx2f(x) = \cos{x^2}.

Let u(x)=x2u(x) = x^2, F(u)=cosuF(u) = \cos u

dfdx=sinu2x=2xsinx2 \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 sinxx\frac{\sin x} x.

Suppose

limxaf(x)=0\lim_{x\rightarrow{a}} f(x) = 0

and

limxag(x)=0\lim_{x\rightarrow{a}} g(x) = 0

and we want limxaf(x)g(x)\lim_{x\rightarrow{a}} \frac{f(x)}{g(x)}.

If

limxaf(x)g(x)=L\lim_{x\rightarrow{a}} \frac{f'(x)}{g'(x)} = L

where any LL is any real number or ±\pm \infty, then

limxaf(x)g(x)=L\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.

when these occur the gradient of the tangent to the curve, f(x)=0f'(x) = 0. The condition f(x)=0f'(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:

Local Maximum

The point x=ax = a is a local maximum if:

f(a)=0 and f(a)<0f'(a) = 0 \text{ and } f''(a) < 0

This is because f(x)f'(x) is a decreasing function of xx near x=ax=a.

Local Minimum

The point x=ax = a is a local minimum if:

f(a)=0 and f(a)>0f'(a) = 0 \text{ and } f''(a) > 0

This is because f(x)f'(x) is a increasing function of xx near x=ax=a.

Point of Inflection

f(a)=0 and f(a)=0 and f(a)0f'(a) = 0 \text{ and } f''(a) = 0 \text { and } f'''(a) \ne 0

f(a)>0f'''(a) > 0

f(a)<0f'''(a) < 0

Approximating with the Taylor series

The expansion

ex=1+x+x22!+x33!+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:

Strategy

Suppose we know information about f(x)f(x) only at the point x=0x=0. How can we find out about ff for other values of xx?

We could approximate the function by successive polynomials, each time matching more derivatives at x=0x=0.

g(x)=a0 using f(0)g(x)=a0+a1x using f(0),f(0)g(x)=a0+a1x+a2x2 using f(0),f(0),f(0)and so on...\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 xx near 0, approximate f(x)=cosxf(x) = \cos x by a quadratic.

  1. Set f(0)=g(0f(0) = g(0:

    f(0)=1g(0)=a0=1f(0) = 1 \rightarrow g(0) = a_0 = 1

  2. Set f(0)=g(0f'(0) = g'(0:

    f(0)=sin0=0g(0)=a1=0f'(0) = -\sin0 = 0 \rightarrow g'(0) = a_1 = 0

  3. Set f(0)=g(0f''(0) = g''(0:

    f(0)=cos=1g(0)=2a2=1a2=0.5f''(0) = -\cos = -1 \rightarrow g''(0) = 2a_2 = -1 \rightarrow a_2 = -0.5

So for xx near 0,

cosx112x2\cos x \approx 1 - \frac 1 2 x^2

Check:

xx cosx\cos x 10.5x21 - 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)f(x) can be written as an infinite Maclaurin Series

f(x)=a0+a1x+a2x2+a3x2+f(x) = a_0 + a_1x + a_2x^2 + a_3x^2 + \cdots

where

a0=f(0)an=1n!dnfdxn|x=0a_0 = f(0) \qquad a_n = \frac 1 {n!} \frac{\mathrm d^nf}{\mathrm dx^n} \bigg|_{x=0}

(|x=0|_{x=0} means evaluated at x=0x=0)

Taylor Series

We may alternatively expand about any point x=ax=a to give a Taylor series:

f(x)=f(a)+(xa)f(a)+12!(xa)2f(a)+13!(xa)3f(a)++1n!(xa)nf(n)(a)\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+hx = a+h where hh is small:

f(a+h)=f(a)+hf(a)++1n!hnf(n)(a)+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=ax=a, then f(a)=0f'(a) = 0 and the Taylor series begins

f(x)=f(a)+12f(a)(xa)2+f(x) = f(a) + \frac 1 2 f''(a)(x-a)^2 + \cdots

Integration

Integration is the reverse of differentiation.

Take velocity and displacement as an example:

vdt=s+c\int\! v \mathrm dt = s + c

where cc is the constant of integration, which is required for indefinite integrals.A

Definite Integrals

The definite integral of a function f(x)f(x) in the range axba \le x \le b is denoted be:

abf(x)dx\int^b_a \! f(x) \,\mathrm dx

If f(x)=F(x)f(x) = F'(x) (f(x)f(x) is the derivative of F(x)F(x)) then

abf(x)dx=[F(x)]ab=F(b)F(a)\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.

Area under curve nf(xn)Δxn\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

nf(xn)Δxnabf(x)dx\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:

y=f1(x)=2x2y=f2(x)=x\begin{align*} y &= f_1(x) = 2 - x^2 \\ y &= f_2(x) = x \end{align*}

  1. Find the crossing points PP and QQ

    f1(x)=f2(x)x=2x2x=1x=2\begin{align*} f_1(x) &= f_2(x) \\ x &= 2-x^2 \\ x &= 1 \\ x &= -2 \end{align*}

  2. Since f1(x)f2(x)f_1(x) \ge f_2(x) between PP and QQ

A=21(f1(x)f2(x))dx=21(2x2x)dx=[2x13x312x2]21=(21312)(4+8342)=92\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=(5x1)3dxI = \int\!(5x - 1)^3 \mathrm dx

  1. Let w(x)=5x1w(x) = 5x - 1

  2. ddxw=515dw=dx\begin{align*} \frac{\mathrm d}{\mathrm dx} w &= 5 \\ \frac 15 \mathrm dw &= \mathrm dx \end{align*}

  3. The integral is then

    I=w315dw=1514w4+c=120w4+c\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 ww out

I=(5x1)420+cI = \frac{(5x-1)^4}{20} + c

Example 2

Find

I=cosxsinx+1dxI = \int\! \cos x \sqrt{\sin x + 1} \mathrm dx

  1. Let

    w(x)=sinx+1w(x) = \sin x + 1

  2. Then

    ddxw=cosxdw=cosxdx\begin{align*} \frac{\mathrm d}{\mathrm dx} w = \cos x \\ \mathrm dw = \cos x \mathrm dx \\ \end{align*}

  3. The integral is now

    I=wdw=w12dw=23w32+c\begin{align*} I &= \int\! \sqrt w \,\mathrm dw \\ &= \int\! w^{\frac12} \,\mathrm dw \\ &= \frac23w^{\frac32} + c \end{align*}

  4. Finally substitute ww out to get:

    I=23(sinx+1)32+cI = \frac23 (\sin x + 1)^{\frac32} + c

Example 3

Find

I=0π2cosxsinx+1dxI = \int^{\frac\pi2}_0\! \cos x \sqrt{\sin x + 1} \,\mathrm dx

  1. Use the previous example to get to

    I=12wdw=23w32+cI = \int^2_1\! \sqrt w \,\mathrm dw = \frac23w^{\frac32} + c

  2. Since w(x)=sinx+1w(x) = \sin x + 1 the limits are:

    x=0w=1x=π2w=2\begin{align*} x = 0 &\rightarrow w = 1\\ x = \frac\pi2 &\rightarrow w = 2 \end{align*}

  3. This gives us

    I=[23w32]12=23(223=1)I = \left[ \frac23w^{\frac32} \right]^2_1 = \frac23 (2^{\frac23} = 1)

Example 4

Find

I=011x2dxI = \int^1_0\! \sqrt{1 - x^2} \,\mathrm dx

  1. Try a trigonmetrical substitution:

x=sinwdxdw=coswdx=cos2dw\begin{align*} x &= \sin w \\ \\ \frac{\mathrm dx}{\mathrm dw} = \cos w \\ \mathrm dx = \cos 2 \,\mathrm dw \\ \end{align*}

  1. x=0w=0x=1w=π2\begin{align*} x=0 &\rightarrow w=0 \\ x=1 &\rightarrow w=\frac\pi2 \end{align*}

  2. Therefore

    I=0π21sin2wcoswdw=0π2coswwdw\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)=2cos2w1\cos(2w) = 2\cos^2w - 1 so:

    cos2w=12cos(2w)+12\cos^2w = \frac12 \cos(2w) + \frac12

    Hence

    I=0π212cos(2w)+12dw=[14sin(2w)+w2]0π2=(14sinπ+π4)0=π4\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=udvdxdx+dudxvdxuv = \int\! u\frac{\mathrm dv}{\mathrm dx} \,\mathrm dx + \int\! \frac{\mathrm du}{\mathrm dx}v \,\mathrm dx

or

udvdxdx=uvdudxvdx\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=lnxdxI = \int\! \ln x \,\mathrm dx

  1. Use

    udvdxdx=uvdudxvdx\int\! u\frac{\mathrm dv}{\mathrm dx} \,\mathrm dx = uv - \int\! \frac{\mathrm du}{\mathrm dx}v \,\mathrm dx

  2. Set u=lnxu = \ln x
    and v=1v' = 1.

  3. This means that u=1xu' = \frac1x and v=xv = x.

  4. I=xlnxx1xdx+c=xlnxdx+c=xlnxx+c\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

dydx=y2\frac{\mathrm dy}{\mathrm dx} = y^2

To find yy, is not a straightforward integration:

y=y2dxy = \int\!y^2 \,\mathrm dx

The equation above does not solve for yy as we can’t integrate the right until we know yy… which is what we’re trying to find.

This is an example of a first order differential equation. The general form is:

dydx=F(x,y)\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

dydx=f(x)g(y)\frac{\mathrm dy}{\mathrm dx} = f(x)g(y)

We can solve these by rearranging:

1g(ydydx=f(x)\frac1{g(y} \cdot \frac{\mathrm dy}{\mathrm dx} = f(x)

1g(y)dy=f(x)dx+c\int\! \frac1{g(y)} \,\mathrm dy = \int\! f(x) \,\mathrm dx + c

Example 1

Find yy such that

dydx=ky\frac{\mathrm dy}{\mathrm dx} = ky

where kk is a constant.

Rearrange to get

1ydy=kdx+clny=kx+cy=ekx+c=ecekx=Aekx\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=ecA = e^c is an arbitrary constant.

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