Fourier Transform and Limit of Euler's Formula

In summary, the conversation on Physics Forums involved discussing the convenient property of continuous Fourier Transforms and different methods of proving it. One method involved using the inverse Fourier Transform and the other involved integrating by parts recursively. There was a question about whether or not the limit of e^{-i \omega x} is 0, but it was clarified that it is the derivatives of f(x) that must decay to 0 at the end points.
  • #1
gordon831
9
0
Hey Physics Forums,

Grading an assignment, the current topic is continuous Fourier Transforms. They're trying to prove the convenient property:
[tex] \mathcal{F} \left[ \frac{d^n}{dx^n} f(x) \right] = (i \omega)^n \mathcal{F} \left[ f(x) \right] [/tex]
So there's a simple way to get it:
Let [itex]f(x)[/itex] be represented by it's Inverse Fourier Transform [itex]f(x) = \mathcal{F}^{-1} \left[ g( \omega ) \right] = \frac{1}{2 \pi} \int_{-\infty}^{\infty} g( \omega )e^{i \omega x} d \omega [/itex]
Then,
[tex] \frac{d^n}{d x^n} f(x) = \frac{d^n}{d x^n} \frac{1}{2 \pi} \int_{-\infty}^{\infty} g( \omega )e^{i \omega x} d \omega = \frac{1}{2 \pi} \int_{-\infty}^{\infty} g( \omega ) \frac{d^n}{d x^n}e^{i \omega x} d \omega = (i \omega)^n \frac{1}{2 \pi} \int_{-\infty}^{\infty} g( \omega ) e^{i \omega x} d \omega = (i \omega)^n \mathcal{F} \left[ f(x) \right] [/tex]

However, I have some people with a different method. They directly transform the entire expression, and apply integration by parts recursively until they obtain:
[tex] \left. (i \omega)^0 \frac{d^{n-1}}{dx^{n-1}}[f(x)]e^{-i \omega x} + (i \omega)^1 \frac{d^{n-2}}{dx^{n-2}}[f(x)]e^{-i \omega x} + \ldots \hspace{10px} \right|^{\infty}_{-\infty} + (i \omega)^n \int f(x) e^{-i \omega x}dx [/tex]

The claim is that when the delimiter is applied, [itex]\lim_{x \to \pm \infty} e^{-i \omega x} = 0[/itex]. I'm not sure if this is true. [itex]e^{-i \omega x} = \cos(\omega x) - i \sin(\omega x)[/itex] which clearly oscillates. Can anyone else confirm this?
 
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  • #2
gordon831 said:
However, I have some people with a different method. They directly transform the entire expression, and apply integration by parts recursively until they obtain:
[tex] \left. (i \omega)^0 \frac{d^{n-1}}{dx^{n-1}}[f(x)]e^{-i \omega x} + (i \omega)^1 \frac{d^{n-2}}{dx^{n-2}}[f(x)]e^{-i \omega x} + \ldots \hspace{10px} \right|^{\infty}_{-\infty} + (i \omega)^n \int f(x) e^{-i \omega x}dx [/tex]

The claim is that when the delimiter is applied, [itex]\lim_{x \to \pm \infty} e^{-i \omega x} = 0[/itex]. I'm not sure if this is true. [itex]e^{-i \omega x} = \cos(\omega x) - i \sin(\omega x)[/itex] which clearly oscillates. Can anyone else confirm this?

It is not the [itex]\exp(i\omega x)[/itex] term which vanishes at the end points, but the derivatives of f(x). Strictly speaking, only functions which decay to zero as the argument grows large have Fourier transforms. Since they decay to zero, their derivatives must decay to zero.

For generalized functions/distributions like the delta function, the identity the students are asked to prove is basically just defined to match the case of legitimately fourier-transformable functions. (Alternatively, the distribution definition includes integration against a smooth test function which decays to zero at the end points).
 
  • #3
Right, forgot Dirichlet conditions. Thanks for the catch!
 

Related to Fourier Transform and Limit of Euler's Formula

1. What is the Fourier Transform?

The Fourier Transform is a mathematical operation that converts a signal from its original domain (usually time or space) to a representation in the frequency domain. It is commonly used in signal processing and image analysis to decompose a signal into its constituent frequencies.

2. What is the significance of Euler's formula in the Fourier Transform?

Euler's formula, e^(ix) = cos(x) + i*sin(x), plays a crucial role in the Fourier Transform as it allows us to represent complex signals in terms of simpler trigonometric functions. This simplification makes it easier to analyze and manipulate signals in the frequency domain.

3. How is the Fourier Transform related to the Limit of Euler's formula?

The Limit of Euler's formula, e^(ix) = cos(x) + i*sin(x), is a special case of the Fourier Transform when the frequency is infinitely large. In this case, the Fourier Transform reduces to a single complex number, representing the amplitude and phase of the signal at that frequency.

4. What are the practical applications of the Fourier Transform and Euler's formula?

The Fourier Transform and Euler's formula have numerous practical applications in fields such as signal processing, image analysis, and data compression. They are also used in physics, engineering, and mathematics to solve differential equations and model physical systems.

5. What are some common misconceptions about the Fourier Transform and Euler's formula?

One common misconception is that the Fourier Transform only applies to periodic signals. In reality, the Fourier Transform can be applied to a wide range of signals, including non-periodic and non-continuous signals. Another misconception is that the Limit of Euler's formula only applies to imaginary numbers. In fact, it can be extended to any real number, providing a useful tool for solving complex problems.

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