Questions related to Fourier Analysis

In summary, Fourier analysis is a mathematical technique used to break down complex signals into individual frequency components. It has various applications in science and is used to analyze and understand the behavior of systems and signals. There are two types of Fourier analysis: discrete and continuous, which are used for different types of signals. The Fourier transform is a tool that enables the application of Fourier analysis techniques. However, there are limitations to Fourier analysis, such as the assumption of periodicity and linearity of the signal being analyzed.
  • #1
xalvyn
17
0
Dear all

I have recently taken up the study of Fourier analysis. My background knowledge is limited - some basic notions of analysis, including the Riemann integral, as well as uniform and pointwise convergence of series of functions. These are not exactly homework problems, but questions that I have been thinking about during the course of my self-study - and to which I have so far not found any satisfactory answers. I would gladly appreciate any help rendered.

Homework Statement



1. Is it true that, if [tex]0 < \theta _0 < \pi[/tex], then [tex]|\sin n\theta _0|[/tex] diverges as [tex]n[/tex] tends to infinity? If so, how should we prove it generally?

2. Suppose that the Fourier series of a continuous function [tex]f(x)[/tex] converges pointwise at [tex]x=x_0[/tex]. Is it necessarily true that [tex]\sum_{i=-\infty}^\infty \hat{f} (n) e^{in x_0} = f(x_0)[/tex]?


Homework Equations





The Attempt at a Solution



1. This seems much easier to prove for individual values of [tex]\theta _0[/tex], but I find it difficult to extend the argument to a general case. I could, however, prove that the value of [tex]|\sin \theta _0|[/tex] does not approach 0: we may show that there exists a [tex]c > 0[/tex] such that there are arbitrarily large values of [tex]n[/tex] satisfying [tex]|\sin n \theta _0| > c > 0.[/tex] Choose [tex]c[/tex] less than [tex]\frac{1}{2}r[/tex] by a very small amount, where [tex]k[/tex] is the largest positive integer satisfying [tex]\pi = k \theta _0 + r[/tex] with [tex]r > 0[/tex]. If, then, [tex]|\sin p \theta _0| \leq c[/tex], it follows that [tex]|\sin (p+1) \theta _0| > c [/tex]. Extending this sort of argument seems more difficult.

2. I could think of a discontinuous function for which the statement is false: the sawtooth function defined by

[tex] f(x) = -\frac{\pi}{2}-\frac{x}{2}[/tex] if [tex] -\pi < x \le 0 [/tex];

[tex] \frac{\pi}{2} - \frac{x}{2}[/tex] if [tex]0 < x < \pi[/tex].

In this case, while the Fourier series of f converges to 0 at [tex]x=0[/tex], the value of [tex]f(0)[/tex] is [tex]-\frac{\pi}{2}[/tex]. I cannot, however, construct an example of a continuous function for which the statement is not true.

Thanks for any help.
 
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  • #2
Answer 1. Yes, it is true that, if 0 < \theta _0 < \pi, then |\sin n\theta _0| diverges as n tends to infinity. This can be proven using the Weierstrass M-Test. By the M-Test, if we can show that there exists a constant c > 0 such that |\sin n \theta _0| > c for all n \in \mathbb{N} then the series \sum_{n=1}^\infty |\sin n \theta _0| must diverge. To show that this holds, note that |\sin n \theta _0| cannot be less than \frac{1}{2} for any values of n. Therefore, we can choose c = \frac{1}{2} and this satisfies the conditions of the M-Test. 2. No, it is not necessarily true that \sum_{i=-\infty}^\infty \hat{f} (n) e^{in x_0} = f(x_0). The Fourier series may converge pointwise at x=x_0, but the value of the limit may be different from f(x_0). For example, consider the function f(x) = 2x - x^2 over the interval [0,\pi]. The Fourier series of f converges pointwise at x=0, but the value of the limit is 0, while f(0) = 0.
 

Related to Questions related to Fourier Analysis

1. What is Fourier analysis?

Fourier analysis is a mathematical technique used to decompose a complex signal or function into its individual frequency components, which can then be analyzed and studied separately. It is based on the idea that any periodic signal can be represented as a combination of simple sine and cosine waves with different frequencies and amplitudes.

2. How is Fourier analysis used in science?

Fourier analysis has many applications in science, including in physics, engineering, and signal processing. It is often used to analyze and understand the behavior of complex systems and signals, such as in the study of sound and vibrations, image processing, and the analysis of geological data.

3. What is the difference between discrete and continuous Fourier analysis?

The main difference between discrete and continuous Fourier analysis is the type of signal or function being analyzed. Discrete Fourier analysis is used for signals that are composed of a discrete set of data points, while continuous Fourier analysis is used for signals that are continuous in time or space. Discrete Fourier analysis is often used in digital signal processing, while continuous Fourier analysis is more commonly used in theoretical and mathematical applications.

4. What is the relationship between Fourier analysis and the Fourier transform?

The Fourier transform is a mathematical operation that converts a signal from the time or spatial domain to the frequency domain, allowing for the application of Fourier analysis techniques. In other words, the Fourier transform is a tool that enables us to perform Fourier analysis on a signal. The Fourier transform can be applied to both discrete and continuous signals.

5. Are there any limitations to Fourier analysis?

While Fourier analysis is a powerful and widely used technique, it does have some limitations. One limitation is that it assumes that the signal being analyzed is periodic, which may not always be the case in real-world applications. Additionally, Fourier analysis is most effective for signals that are linear and stationary, meaning that they do not change over time. Nonlinear and non-stationary signals may require more advanced techniques for analysis.

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