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This video is to give you more
examples of Fourier series.

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I'll start with a
function that's odd.

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My odd function means that
on the left side of 0,

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I get the negative of what I
have on the right side of 0.

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F at minus x is minus f of x.

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And it's the sine
function that's odd.

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The cosine function is even, and
we will have no cosines here.

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All the integrals
that involve cosines

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will tell us 0 for
the coefficients AN.

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What we'll get is
the B coefficients,

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the sine functions.

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So you see that I chose a simple
odd function, minus 1 or 1,

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which would give a square
wave if I continue it on.

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It will go down, up, down,
up in a square wave pattern.

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And I'm going to express
that as a combination

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of sine functions, smooth waves.

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And here was the
formula from last time

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for the coefficients
bk, except now I'm

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only integrating over
half, over the zero

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to pi part of the
interval, so I double it.

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So that's an odd function,
that's an odd function.

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When I multiply them, I
have an even function.

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And the integral
from minus pi to 0

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is just the same as the
integral from 0 to pi.

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So I'll do only 0 to
pi and multiply by 2.

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But my function on 0 to pi is 1.

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My nice square wave
is just plus 1 there,

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so I'm just
integrating sine kx dx.

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We can do this.

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It's minus cosine kx
divided by k, right?

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That's the integral with
the 2 over pi factor.

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Now I have to put
in pi and 0 and put

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in the limits of integration
and get the answer.

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So what do I get?

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I get 2 over pi.

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For k equal 1, I think
I get-- so k is 1,

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the denominator will be 1, and
I think the numerator is 2.

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Yes, when k is 0, I get yeah.

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When k is 1, I get 2.

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When k is 2, so
this is 4 over pi,

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I figured out as the
first coefficient.

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The coefficient b1 is 4 over pi.

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The coefficient b2, now if I
take k equal to 2, I have a 2

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down below.

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But above, I have a 0
because the cosine of 2 pi

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is the same as the cosine of 0.

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When I subtract I get
nothing, so that's 0.

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Now I go to k equals 3.

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So the k equals 3
will come down here.

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And now when k is 3, it turns
out I get-- they don't cancel,

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they reinforce.

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I get another 2.

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Good if you do these.

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And when k is 4,
I get a 0 again.

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You see the pattern?

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The pattern for the integrals
is the k is going 1, 2, 3, 4, 5.

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This part gives me a 2 or
a 0 or a 2 or a 0 in order.

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If you check that,
you'll get it.

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So I see that now for this
function, which is better

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than the delta function also.

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It's not very smooth.

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It has jumps.

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It's a jump function,
a step function.

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I see some decay,
some slow decay,

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in the Fourier coefficients.

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This factor k is growing so
the numbers are going to 0,

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but not very fast.

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Not very fast.

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Because my function
is not very smooth.

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So now you see-- so if
I use those numbers,

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I'm saying that the square wave,
this function, the minus 1 to 1

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function, is equal
to, let's see.

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I might as well take
that 4 over pi times 1.

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So that's 1 sine x, 0, sine 2x's
then 4 over pi sine 3x's, but

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with this guy there's
a 3, 0 sine 4x's,

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sine 5x comes in
over 5, and so on.

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That's a kind of nice example.

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It turns out that we have
just the odd frequencies 1, 3,

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5 in the square wave and
they're multiplied by 4 over pi

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and they're divided by the
frequency, so that's the decay.

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There is an odd function.

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Why don't I integrate
that function?

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If I want to get
an even function

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to show you an even
example, I'll just

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integrate that square wave.

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When I integrate it square
wave, it'll be even.

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Maybe I'll start the integral
at 0, then it goes up at 1.

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And here the integral is
negative, so it's coming down.

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So you see it's a-- what am I
going to call this function?

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Sort of a repeating
ramp function.

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It's a ramp down and then
up, down and then up.

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But of course from minus pi to
pi, that's where I'm looking.

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I'm looking between
minus pi and pi.

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And I see that function is even.

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And what does even mean?

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That means that my
function at minus--

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there is minus x-- is the
same as the value at x.

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And what that means for a
Fourier series is cosine.

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Even functions only
have cosine terms.

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And of course, since
I've just integrated,

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I might as well just
integrate that series.

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So this is this ramp, this
repeating ramp function,

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is going to be 4 over pi.

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I could figure out the
cosine coefficients,

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the a's, patiently.

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But why should I do that
when I can just integrate?

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So the integral of
sine x will be minus

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is the integral of
sine x, is minus cosine

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x, so I'll put the minus
there, cosine x over 1 I guess.

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Now what's the integral of this?

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The integral of sine 3x
is a cosine 3x over 3.

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And there's another
3 and there's

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a minus sign, which I've got.

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So I think it's cosine
of 3x over 3 squared,

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because I have one 3
there and I get another 3

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from the integration.

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And similarly here,
when I integrate sine 5x

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I get cos 5x with a 5.

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And then I already had
one 5, so 5 squared.

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So there you go.

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[LAUGHTER]

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There's something in freshman
calculus which I totally

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forgot, the constant term.

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So there is a constant term,
the average value, that a0.

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I've only found
the a1, 2, 3, 4, 5.

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I haven't found the a0, and that
would be the average of that.

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I don't know, what's the
average of this function?

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Its goes from 0 up
to pi and it seems

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like it's pretty-- I didn't
draw it well, but half way.

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I think probably its average
is about pi over 2, right?

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Let's hope that's right.

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So let me sneak in the
constant term here.

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The ramp is, I think I have
a constant term is pi over 2.

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That's the average value.

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It would come from the
formula and those-- well,

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what do you see now?

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That's the other example
I wanted you to see.

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You see a faster drop off.

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1, 9, 25, 49, whatever.

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It's dropping off
with k squared.

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And the reason it drops
off faster than this one

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is that it's smoother.

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This function has corners.

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This function has jumps.

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So a jump is one level
more rough, more word

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noisy than a ramp function.

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The smoother function
has faster decay.

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Smooth-- let me
write those words--

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smooth function connects
with faster decay.

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Faster drop off of the
Fourier coefficient.

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It means that the Fourier
series is much more useful.

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Fourier series is really
terrific for functions

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that are smooth because then you
only need to keep a few terms.

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For functions that have
jumps or delta functions,

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you have to keep
many, many terms

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and the Fourier
series calculation

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is much more difficult.

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So that's the second example.

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Let's see, what
more shall I say?

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We learned something
about integrating

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and taking the
derivative so let me

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end with just two basic rules.

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Two basic rules.

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So the rule for derivatives.

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What's the Fourier
series of df dx?

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And the second will
be the rule for shift.

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What's the Fourier series
for f of x minus a shift?

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You know that when I change
x to x minus d, all that does

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is shift the graph
by a distance d.

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That should do something nice
to its Fourier coefficient.

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So I'm starting with--
oh, I haven't given you

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any practice with
a complex case.

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This would be a good time.

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Suppose start is f of
x equals the sum of ck,

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a complex coefficient e to the
ikx, the complex exponential.

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And you'll remember that
sum went from minus infinity

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to infinity.

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So I have a Fourier series.

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I'm imagining I know the
coefficients and I want to say,

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what happens if I
take the derivative?

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Well, just take the derivative.

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You'll have a sum of the
derivative brings down

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a factor ik.

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So that's the rule.

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Simple, but important.

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That's why Fourier series
is so great because you

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have orthogonality and then
you have this simple rule

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with derivatives.

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it just brings a factor
ik so the derivative

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make sure function noisier and
you have larger coefficients.

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And if I do f of
x minus d, so I'll

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change x to x minus d, so I'll
see the sum of ck e to the ikx,

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e to the minus ikd, right?

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I've put in x minus
d instead of x.

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And here I see that the Fourier
coefficient for a shifted

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function-- so the ck was a
Fourier coefficient for f.

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When I shift f, it
multiplies that coefficient

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by a phase change.

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The magnitude stayed
the same because that's

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a number-- everybody recognizes
that as a number of magnitude 1

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and just has a phase shift.

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Those are two would
rules that show

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why you can use Fourier series
in differential equations

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and in difference equations.

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Thank you.