Proving Continuity of a Fourier Series Function

In summary, the conversation discusses a function f:R²-->R and its continuity. The speaker shares a hint about using the fact that a linear combination of continuous functions is continuous, but the original poster points out that it does not apply to an infinite sum. However, the hint leads the original poster to remember a theorem and generalize it to solve the problem. The conversation then shifts to finding the sum of f(3\pi / 4, -5\pi /4), but the original poster is unsure how to proceed. Eventually, they solve the problem.
  • #1
quasar987
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I'm puzzled and don't know where to begin with this question; it goes like

"Consider the function f:R²-->R defined by

[tex]f(x,y) = \sum_{n=1}^{\infty}\frac{(-1)^n}{n^2}sin(nx)sin(ny)[/tex]

Show that f is continuous."

Any hint?

.
 
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  • #2
if you can use the fact that a linear combination of continuous functions is continuous, then the problem is greatly simplified--it becomes a matter of showing that sin(nx)sin(xy) is continuous for any n.


...maybe?
 
  • #3
Hey Brad, I appreciate your interest in my problem, however, I don't think an infinite sum qualifies as a linear combination. Nevertheless, your idea made me remember a theorem of 1 variable analysis and I was able to generalize it to an n variable function which solves the problem. :)
 
  • #4
glad i could be of indirect service! :biggrin:
 
  • #5
Next they say "evaluate [itex]f(3\pi / 4, -5\pi /4)[/itex]". I realize that this is just

[tex]\sum_{n=1}^{\infty} \frac{(-1)^n}{n^2} sin^2(\frac{3n \pi }{4})[/tex]

but how do I find the sum? I tried squeezing the sum btw 0 and [itex]\sum (-1)^n/n^2[/itex] but this sum is not 0, so I can't conclude. After this attemp I'm all out of idea.
Any help welcome.
 
  • #6
Solved.
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FAQ: Proving Continuity of a Fourier Series Function

1. What is Fourier analysis and why is it important?

Fourier analysis is a mathematical technique used to decompose a complex signal into simpler components. It is important because it allows us to better understand and analyze signals and patterns in various fields such as physics, engineering, and data analysis.

2. What is the Fourier transform and how is it different from Fourier series?

The Fourier transform is a mathematical operation that converts a signal from the time domain to the frequency domain. It is different from Fourier series, which is a representation of a periodic signal as a sum of simple sinusoidal functions. The Fourier transform can be used for non-periodic signals, while Fourier series is only applicable to periodic signals.

3. How is Fourier analysis used in image processing?

Fourier analysis is commonly used in image processing to enhance and filter images. By converting an image into its frequency components, we can remove unwanted noise and distortions and improve image quality.

4. Can Fourier analysis be applied to non-linear systems?

Yes, Fourier analysis can be applied to non-linear systems, but it becomes more complex as the system becomes more non-linear. In some cases, the Fourier transform may not be useful for analyzing non-linear systems, and other techniques such as wavelet analysis may be more appropriate.

5. What are some real-world applications of Fourier analysis?

Fourier analysis has many practical applications, including signal processing, audio and image compression, data compression, and spectral analysis in various fields such as physics, engineering, and mathematics. It is also used in medical imaging, weather forecasting, and speech recognition.

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