How to find the sum of two series using the Weierstrass M-test?

But this does not mean that it converges uniformly. To check that it converges uniformly we need to use the M-test, that is, find a sequence (M_n) such that|M_n| \geq |a_n| \mbox{ for all } nand \sum_{n=1}^{\infty} M_n converges. Then we can conclude that \sum_{n=1}^{\infty} |a_n| converges, and therefore that the series converges uniformly. So, in our case, we have|M_n| =
  • #1
Hummingbird25
86
0
Hi

Given the function [tex]f(t) = t^2[/tex], were [tex]t \in ]- \pi, pi[[/tex], and is continious find the Fourier series for f(t). [tex]L = 2 \pi[/tex].

Then

[tex] A_0 = \frac{1}{2 \pi} \int \limit_{-\pi} ^{\pi} t^2 dt = \frac{\pi ^2}{3}[/tex]

[tex]A_n = \int \limit_{-\pi} ^{\pi} t^2 \cdot cos(\matrm{n} \pi \mathrm{t}) dt[/tex]

[tex]A_n = \int \limit_{-\pi} ^{\pi} u^2 \cdot cos(u) du[/tex], where u = n \pi t,

The new limit gives:

[tex]A_n = \int \limit_{0} ^{2 \pi^2 n} u^2 \cdot cos(u) du[/tex]

[tex]A_n = [u^2 \cdot sin(u) - 2sin(u) + 2u sin(u)]_{0} ^{2 \pi ^ 2 n}[/tex]

Then

[tex]B_n = \int \limit_{0} ^{2n \pi^2} u^2 \cdot sin(u) du[/tex]

which gives

[tex]B_n = (2-4n^2 * \pi ^4 * cos(2n * \pi ^2) + 4n *sin (2n * \pi ^2) \pi ^2 -2[/tex]

Therefore the Fourier series for f(t) is:

[tex]\frac{\pi ^ 2}{3} + \sum \limit_{n=1} ^{\infty} A_n cos(nt) + B_n sin(nt)[/tex]

Could someone please me if my calculations are correct?

Sincerley

Yours
Hummingbird
 
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  • #2
you may check here that the Fourier coefficients ought to be

[tex]A_0=\frac{1}{\pi}\int_{-\pi}^{\pi}f(t) dt[/tex]

[tex]A_n=\frac{1}{\pi}\int_{-\pi}^{\pi}f(t)\cos (nt) dt[/tex]

and

[tex]B_n=\frac{1}{\pi}\int_{-\pi}^{\pi}f(t)\sin (nt) dt[/tex]

so that

for [tex]f(t)=t^2[/tex] we have

[tex]A_0=\frac{1}{\pi}\int_{-\pi}^{\pi}t^2 dt = \frac{2}{\pi}\int_{0}^{\pi}t^2 dt = \frac{2\pi ^3}{3}[/tex]

where the second move is from the integral of an even function over a symmetric interval (i.e. [-a,a]) is twice the integral over [0,a], also note that the same applies to An, hence

[tex]A_n=\frac{1}{\pi}\int_{-\pi}^{\pi}t^2 \cos (nt) dt = \frac{2}{\pi}\int_{0}^{\pi}t^2 \cos (nt) dt[/tex]

integrate by parts twice to get EDIT: forgot to multiply by the [tex]\frac{1}{\pi}[/tex]!

[tex]A_n=\frac{2}{\pi}\int_{0}^{\pi}t^2 \cos (nt) dt = \frac{2}{\pi}\left[ \frac{2t^2}{n}\sin (nt) + \frac{4t}{n^2}\cos (nt)-\frac{4}{n^3}\sin (nt)\right]_{t=0}^{\pi} = \frac{1}{\pi}\left( \frac{2\pi ^2}{n}\sin (n\pi ) + \frac{4\pi}{n^2}\cos (n\pi )-\frac{4}{n^3}\sin (n\pi )\right) [/tex]
[tex] = \frac{2\pi }{n}\sin (n\pi ) + \frac{4}{n^2}\cos (n\pi )-\frac{4}{\pi n^3}\sin (n\pi )[/tex]

know also that [tex]t^2\sin (nt)[/tex] is an odd function, and that the integral of an odd function over a symmetric interval (i.e. [-a,a]) is zero, hence

[tex]B_n=\frac{1}{\pi}\int_{-\pi}^{\pi}t^2\sin (nt) dt=0[/tex]
 
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  • #3
Notably, you may perform definite integration on this http://www.hostsrv.com/webmab/app1/MSP/quickmath/02/pageGenerate?site=quickmath&s1=calculus&s2=integrate&s3=advanced
 
Last edited by a moderator:
  • #4
Hello ben,

I guess it mixed up the details from a textbook example. Sorry,

Then the Fourier series is expressed:

[tex]\frac{2\pi ^3}{3} + \sum \limit_{n=1} ^{\infty} \frac{2\pi ^2}{n}\sin (n\pi ) + \frac{4\pi}{n^2}\cos (n\pi )-\frac{4}{n^3}\sin (n\pi )[/tex] ?

Sincerely
Hummingbird25

benorin said:
you may check here that the Fourier coefficients ought to be

[tex]A_0=\frac{1}{\pi}\int_{-\pi}^{\pi}f(t) dt[/tex]

[tex]A_n=\frac{1}{\pi}\int_{-\pi}^{\pi}f(t)\cos (nt) dt[/tex]

and

[tex]B_n=\frac{1}{\pi}\int_{-\pi}^{\pi}f(t)\sin (nt) dt[/tex]

so that

for [tex]f(t)=t^2[/tex] we have

[tex]A_0=\frac{1}{\pi}\int_{-\pi}^{\pi}t^2 dt = \frac{2}{\pi}\int_{0}^{\pi}t^2 dt = \frac{2\pi ^3}{3}[/tex]

where the second move is from the integral of an even function over a symmetric interval (i.e. [-a,a]) is twice the integral over [0,a], also note that the same applies to An, hence

[tex]A_n=\frac{1}{\pi}\int_{-\pi}^{\pi}t^2 \cos (nt) dt = \frac{2}{\pi}\int_{0}^{\pi}t^2 \cos (nt) dt[/tex]

integrate by parts twice to get

[tex]A_n=\frac{2}{\pi}\int_{0}^{\pi}t^2 \cos (nt) dt = \left[ \frac{2t^2}{n}\sin (nt) + \frac{4t}{n^2}\cos (nt)-\frac{4}{n^3}\sin (nt)\right]_{t=0}^{\pi} = \frac{2\pi ^2}{n}\sin (n\pi ) + \frac{4\pi}{n^2}\cos (n\pi )-\frac{4}{n^3}\sin (n\pi )[/tex]

know also that [tex]t^2\sin (nt)[/tex] is an odd function, and that the integral of an odd function over a symmetric interval (i.e. [-a,a]) is zero, hence

[tex]B_n=\frac{1}{\pi}\int_{-\pi}^{\pi}t^2\sin (nt) dt=0[/tex]
 
  • #5
Hummingbird25 said:
Hello ben,

I guess it mixed up the details from a textbook example. Sorry,

Then the Fourier series is expressed:

[tex]\frac{2\pi ^3}{3} + \sum \limit_{n=1} ^{\infty} \frac{2\pi ^2}{n}\sin (n\pi ) + \frac{4\pi}{n^2}\cos (n\pi )-\frac{4}{n^3}\sin (n\pi )[/tex] ?

Sincerely
Hummingbird25

Rather it is expressed:

[tex]\frac{1}{2}A_0+\sum_{n=1}^{\infty} A_n\cos (nt)+ \sum_{n=1}^{\infty} B_n\sin (nt)=\frac{\pi ^3}{3} + \sum \limit_{n=1} ^{\infty} \left( \frac{2\pi ^2}{n}\sin (n\pi ) + \frac{4\pi}{n^2}\cos (n\pi )-\frac{4}{n^3}\sin (n\pi )\right) \cos (nt)[/tex]
 
  • #6
Okay I get that,

By the way,

f(t) has continious deriatives, and is periodic [tex]2 \pi[/tex]

Then the Fourier series of f(t) converge to f(t) Uniformly on [tex]]-\pi, \pi[[/tex] ??

Or am I missing a condition?

Sincerely

Hummingbird

benorin said:
Rather it is expressed:

[tex]\frac{1}{2}A_0+\sum_{n=1}^{\infty} A_n\cos (nt)+ \sum_{n=1}^{\infty} B_n\sin (nt)=\frac{\pi ^3}{3} + \sum \limit_{n=1} ^{\infty} \left( \frac{2\pi ^2}{n}\sin (n\pi ) + \frac{4\pi}{n^2}\cos (n\pi )-\frac{4}{n^3}\sin (n\pi )\right) \cos (nt)[/tex]
 
  • #7
I forgot to distribute the [tex]\frac{1}{\pi}[/tex] in the calculation of A_n in my first post, I fixed it: look for the EDIT,

very important simplifications: [tex]\sin (n\pi ) = 0\mbox{ for }n=1,2,3,...[/tex]

and

[tex]\cos (n\pi ) = (-1)^{n}\mbox{ for }n=1,2,3,...[/tex]

and hence [tex]A_n = \frac{2\pi }{n}\sin (n\pi ) + \frac{4}{n^2}\cos (n\pi )-\frac{4}{\pi n^3}\sin (n\pi ) = \frac{4}{n^2}(-1)^{n}[/tex]

so the series becomes

[tex]\frac{\pi ^3}{3} + \sum \limit_{n=1} ^{\infty} \left( \frac{2\pi }{n}\sin (n\pi ) + \frac{4}{n^2}\cos (n\pi )-\frac{4}{\pi n^3}\sin (n\pi )\right) \cos (nt ) = \frac{\pi ^3}{3} + \sum \limit_{n=1} ^{\infty} (-1)^{n}\frac{4}{n^2}\cos (nt )[/tex]

that is

[tex]\boxed{t^2 \sim \frac{\pi ^3}{3} + 4\sum \limit_{n=1} ^{\infty} (-1)^{n}\frac{\cos (nt)}{n^2} = \frac{\pi ^3}{3} -4\left( \frac{\cos (t)}{1^2}-\frac{\cos (2t)}{2^2}+\frac{\cos (3t)}{3^2}-\mdots \right)}[/tex]​
 
  • #8
Uniform convergence can be proved by the Weierstrass M-test, just note that

[tex] \left| (-1)^{n}\frac{\cos (nt)}{n^2} \right| \leq \frac{1}{n^2}=M_n[/tex] for all n

and [tex]\sum \limit_{n=1} ^{\infty}M_n=\sum \limit_{n=1} ^{\infty}\frac{1}{n^2} [/tex] converges, so the given series converges uniformly on [tex] \left[ -\pi ,\pi \right] [/tex] by the Weierstrass M-test.
 
  • #9
benorin said:
Uniform convergence can be proved by the Weierstrass M-test, just note that

[tex] \left| (-1)^{n}\frac{\cos (nt)}{n^2} \right| \leq \frac{1}{n^2}=M_n[/tex] for all n

and [tex]\sum \limit_{n=1} ^{\infty}M_n=\sum \limit_{n=1} ^{\infty}\frac{1}{n^2} [/tex] converges, so the given series converges uniformly on [tex] \left[ -\pi ,\pi \right] [/tex] by the Weierstrass M-test.

Okay thank You then I only have one final question.

Given the two series

[tex]\sum_{k=1} ^{\infty} \frac{1}{k^4}[/tex]

and

[tex]\sum_{k=1} ^{\infty} (-1)^{k-1} \frac{1}{k^2}[/tex]

I need to find the sum of these two.

In series number 1:

I can see that by the test of comparison, that it converges

[tex]\frac{1}{k^{2+t}} < \frac{1}{k^{2}}[/tex]

But what is the next step in finding the sum here?

In series two:

What do I here? Do I test for convergens ?

Sincerely
Hummingbird
 

Related to How to find the sum of two series using the Weierstrass M-test?

1. What is a Fourier series?

A Fourier series is a mathematical representation of a periodic function as a sum of sine and cosine functions. It is used to decompose a complex signal into simpler components, making it easier to analyze.

2. How is a Fourier series calculated?

A Fourier series is calculated by using the Fourier coefficients, which are determined by integrating the function over one period and then solving for the coefficients using the orthogonality of sine and cosine functions.

3. What is the significance of Fourier series in science?

Fourier series have many applications in science, including signal processing, image and sound compression, and solving differential equations. They also help in understanding the periodic behavior of physical phenomena.

4. Can a non-periodic function have a Fourier series?

No, a non-periodic function cannot have a Fourier series because the fundamental assumption of a Fourier series is that the function is periodic. However, non-periodic functions can be approximated by using a Fourier series with a very large number of terms.

5. What are some common applications of Fourier series?

Some common applications of Fourier series include analyzing and filtering signals in communication systems, image and sound processing, and solving partial differential equations in physics and engineering. They are also used in fields such as finance, biology, and music theory.

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