Where does the Fourier series converge?

In summary, the conversation is about finding the Fourier series of a specific function and determining the function at which the series converges. The conversation also touches on the use of a theorem for piecewise continuous functions. The final conclusion is that the calculations and steps taken are correct.
  • #1
mathmari
Gold Member
MHB
5,049
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Hey! :eek:

I want to find the Fourier series of the following function :

$$g: [-\pi, \pi]\rightarrow \mathbb{R} \\ g(x)=\left\{\begin{matrix}
-\frac{\pi+x}{2} & , -\pi \leq x \leq 0\\
\frac{\pi-x}{2} & , 0<x\leq \pi
\end{matrix}\right.$$

I have done the following:

$$g \sim \frac{a_0}{2}+\sum_{k=1}^{\infty}(a_k \cos (kx)+b_k \sin (kx))$$

$$a_k=\frac{1}{\pi}\int_{\pi}^{\pi} g(x) \cos (kx)dx=\frac{1}{\pi}\int_{-\pi}^0-\frac{\pi+x}{2}\cos (kx)dx+\frac{1}{\pi}\int_0^{\pi}\frac{\pi-x}{2}\cos (kx)dx=\dots=0, k=0, 1, 2, 3, 4, 5, \dots $$

$$b_k=\frac{1}{\pi}\int_{-\pi}^{\pi}g(x)\sin (kx)dx=\frac{1}{\pi}\int_{-\pi}^0-\frac{\pi+x}{2}\sin (kx)dx+\frac{1}{\pi}\int_0^{\pi}\frac{\pi-x}{2}\sin (kx)dx =\dots=\frac{1}{k}, k=1, 2, 3, 4, 5, \dots $$

So, $$g \sim \sum_{k=1}^{\infty}\frac{1}{k}\sin (kx)$$

Is this correct??

How can I find the function at which the Fourier series of $g$ converges?? Do we have to use the following theorem:

Let $f: [0, 2 \pi] \rightarrow \mathbb{R}$ piecewise $C^1[0, 2\pi]$, and $$f \sim \frac{a_0}{2}+\sum_{k=1}^{\infty}(a_k \cos (kx)+b_k \sin (kx))$$

Then $$\frac{a_0}{2}+\sum_{k=1}^{\infty}(a_k\cos (kx)+b_k \sin (kx))=\left\{\begin{matrix}
\frac{f(x^+)+f(x^-)}{2} & , \forall x \in (0,2\pi)\\
\frac{f(0^+)+f(2\pi^-)}{2} & , \forall x \in \{0, 2\pi\}
\end{matrix}\right.$$

?? (Wondering) Is it then as followed??

$$\sum_{k=1}^{\infty}\frac{1}{k}\sin (kx)=\left\{\begin{matrix}
\frac{g(x^+)+g(x^-)}{2}=g(x) & , \forall x \in (-\pi, 0)\\
\frac{g(x^+)+g(x^-)}{2}=g(x) & , \forall x \in (0, \pi)\\
\frac{g(0^+)+g(0^-)}{2}=\frac{\frac{\pi}{2}-\frac{\pi}{2}}{2}=0 & , x=0
\end{matrix}\right.$$
 
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  • #2
mathmari said:
$$g \sim \sum_{k=1}^{\infty}\frac{1}{k}\sin (kx)$$ $$\sum_{k=1}^{\infty}\frac{1}{k}\sin (kx)=\left\{\begin{matrix}
\frac{g(x^+)+g(x^-)}{2}=g(x) & , \forall x \in (-\pi, 0)\\
\frac{g(x^+)+g(x^-)}{2}=g(x) & , \forall x \in (0, \pi)\\
\frac{g(0^+)+g(0^-)}{2}=\frac{\frac{\pi}{2}-\frac{\pi}{2}}{2}=0 & , x=0
\end{matrix}\right.$$
Correct both times. (Star) (Star)
 

1. What is the Fourier series and how is it used?

The Fourier series is a mathematical representation of a periodic function in terms of sine and cosine waves. It is used to approximate a given function by breaking it down into simpler components, making it easier to analyze and manipulate.

2. Why is it important to know where the Fourier series converges?

The convergence of the Fourier series determines the accuracy of the approximation to the original function. It is important to know where it converges in order to determine if the series is a valid representation of the function and to what extent it can be used in calculations.

3. What factors affect the convergence of the Fourier series?

The convergence of the Fourier series is affected by the regularity of the function, the number of terms included in the series, and the choice of basis functions. It also depends on the type of convergence being considered, such as pointwise or uniform convergence.

4. Does the Fourier series always converge?

No, the Fourier series may not converge for all functions. It is only guaranteed to converge for functions that are periodic, continuous, and have a finite number of discontinuities. For functions that do not meet these criteria, the series may still converge in certain cases, but it is not guaranteed.

5. How is the convergence of the Fourier series tested?

The convergence of the Fourier series can be tested using various methods, such as the Cauchy convergence test, the Dirichlet test, or the Abel-Poisson test. These tests can determine if the series converges pointwise, uniformly, or in some other sense. The choice of test will depend on the specific function and its properties.

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