Can the Fourier Transform of an L^1 Function be Bounded by its L^1 Norm?

In summary, the conversation discusses how to show that if ##f \in L^1(ℝ^n)##, then ##||\hat f||_{C^0(ℝ^n)} \le ||f||_{L^1(ℝ^n)}##. It is mentioned that ##\hat f \in C^0(ℝ^n)## can be shown using the dominated convergence theorem, but the proof is incomplete. The conversation then discusses various approaches to finishing the proof, including using the fact that ##\hat f## is max at 0 if ##f## is non-negative. The conversation concludes with a proposed solution and a request for confirmation of its correctness.
  • #1
dRic2
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Hi, I have to show that if ##f \in L^1(ℝ^n)## then:
$$ ||\hat f||_{C^0(ℝ^n)} \le ||f||_{L^1(ℝ^n)}$$
Since ##|f(y)e^{-2 \pi i ξ ⋅y}| \le |f(y)|##, using the dominated convergence theorem, it is possible to show that ##\hat f \in C^0(ℝ^n)## but now I don't know how to go on.

Thanks is advance.
 
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  • #2
##\hat{f}(0)=\int f## should give the result. If ##f\ge 0##, then ##\hat{f}## is max at 0. I'm not sure how to finish.
 
  • #3
I'm very sorry for the late reply. I don't see why
mathman said:
If f≥0f≥0f\ge 0, then ^ff^\hat{f} is max at 0. I'm not sure how to finish.
.
If that is true I think I solved it, but I don't know how to prove your statement.

PS: In the book I'm reading the author says the result can be achieved without knowing that ##\hat f## goes to ##0## at ##\infty##, which he later proves using the result of this proof.
 
  • #4
I think I got it! Here is my solution, hope you can tell me if it is correct. (Here I worked in ℝ for the sake of simplicity)

$$|\hat f(ξ)| = \left| \int_ℝ f(y)e^{-2\pi i ξ y}dy \right| \le \int_ℝ |f(y)e^{-2\pi i ξ y}|dy \le \int_ℝ|f(y)|dy = ||f||_{L^1(ℝ)}$$

So basically here I've proved that ##|\hat f(ξ)|## is less than a constant (##||f||_{L^1(ℝ)}##) then, even more so, ##\max_{ξ \in ℝ} |\hat f(ξ)| \le ||f||_{L^1(ℝ)}##. This proves the original statement and from here we can also conclude that ##\hat f## is limited.

Am I correct?
 
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1. What is the Fourier transform?

The Fourier transform is a mathematical operation that decomposes a function or signal into its constituent frequencies. It is widely used in many fields of science and engineering, including signal processing, image processing, and quantum mechanics.

2. How does the Fourier transform work?

The Fourier transform works by breaking down a function or signal into its individual frequency components. It does this by representing the function as a sum of sinusoidal waves with different amplitudes and frequencies. This allows for a better understanding of the underlying patterns and properties of the function.

3. What is the importance of the Fourier transform in science?

The Fourier transform has many practical applications in science, such as filtering out noise in signals, analyzing the frequency content of a signal, and solving differential equations. It also plays a crucial role in understanding and describing physical phenomena, such as waves and oscillations.

4. Can the Fourier transform be used for any type of signal?

Yes, the Fourier transform can be applied to any signal, whether it is continuous or discrete, periodic or aperiodic. However, some signals may require modifications or additional techniques to obtain accurate results.

5. Are there any limitations to the Fourier transform?

While the Fourier transform is a powerful tool, it does have some limitations. One limitation is that it assumes the signal is stationary, meaning its properties do not change over time. Additionally, it may not be suitable for signals with sharp discontinuities or those that are highly localized in time or frequency.

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