Fourier Series and Dirichlet Conditions: Investigating Convergence

In summary, the conversation was about whether a function that does not satisfy all of Dirichlet's conditions can still be represented by a Fourier series. It was established that Dirichlet's conditions are only sufficient, not necessary conditions, and there are counterexamples where the function does not meet these requirements but still has a convergent Fourier series. The difference between the Weak and Strong Dirichlet conditions was also discussed. Ultimately, the answer to the question depends on the specific conditions and cannot be determined without them.
  • #1
Benny
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I have a question about Fourier series that I would like some help with. If there is a function f(t) which does not satisfy all of Dirichlet's conditions then can its Fourier series still represent it? All I've got is that if all of Dirichlet's conditions are satisified by f(t) then the Fourier series converges to f.

There isn't anything which says that if not all of conditions are satisfied then the Fourier series cannot converge to the function f(t). So I'm having trouble drawing a conclusion. Can someone help me out? Thanks.
 
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  • #2
What you have said is exactly right. Let me express it in a more precise way. The Dirichlet's conditions are only sufficient, not necessary conditions. If a function f(t) meets these requirements then we know that we can express it as a Fourier series. However, if even if f(t) does not meet these requirements, we may still be able to express it as a Fourier series.
 
  • #3
There are two possible meanings of "represent" in your post. The Weak Dirichlet condition (integral of the absolute value of the function is finite) says the Fourier series exists - i.e. you can calculate all the coefficients because the all the integrals that define them are finite.

The Strong Dirichlet condition (a finite number of extrema and a finite number of finite discontinuties) implies the Fourier series also converges to the original function (except at the discontinuities).

As Swapnil said these are not necessary conditions, and there are counterexamples. E.g the periodic function defined by x sin (1/x) in the interval -pi to pi has an infinite number of extrema, but there's no obvious reason (at least to me) why it doesn't have a convergent Fourier series.
 
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  • #4
I'm suprised that someone decided to answer this question after such a long time. I was referring to the "strong" Dirichlet conditions but the source from which my question arose didn't really specify the type of Dirichlet conditions (but the type was implied), which is why I didn't state the specific conditions. Anyway, I found the answer to my question a while ago but thanks for providing more extended answers.
 

FAQ: Fourier Series and Dirichlet Conditions: Investigating Convergence

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 analyze and approximate functions that repeat over a specific interval.

What are Dirichlet conditions?

Dirichlet conditions are a set of mathematical conditions that must be satisfied for a Fourier series to accurately represent a function. These conditions include the function being periodic, having a finite number of discontinuities, and having bounded variation.

How do you investigate the convergence of a Fourier series?

To investigate the convergence of a Fourier series, one can use various tests such as the Dirichlet test, Abel's test, or the Weierstrass M-test. These tests can determine if the series converges absolutely or conditionally.

What is absolute convergence in Fourier series?

Absolute convergence in Fourier series means that the series converges for all values of x, regardless of the choice of the coefficients. This type of convergence ensures that the series will accurately represent the original function.

How are Fourier series used in practical applications?

Fourier series are used in many practical applications, such as signal processing, image and sound compression, and solving differential equations. They can also be used to analyze and approximate physical phenomena such as heat transfer, vibration, and electromagnetic waves.

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