Problem with Fourier Transform

In summary, we are given the problem of proving that the Fourier transform of g(x) is equal to (1/lambda)e^(ik/lambda) times the Fourier transform of f(x), given that g(x) is defined as f(lambda*x+y). After providing the Fourier transforms of f(x) and g(x), the solution is found by applying the definition of a Fourier transform to g(x) and making a substitution to simplify the integral. This yields the desired result.
  • #1
dimensionless
462
1
Here's my problem:
Suppose that f is an integrable function. If [tex]\lambda \ne 0[/tex] is a real number and [tex] g(x) = f(\lambda x + y)[/tex] proove that

[tex]
G(k) = \frac{1}{\lambda} e^{ik/\lambda}F(\frac{k}{\lambda})
[/tex]

Where F and G are the Fourier transforms of f and g, respectively.

I've got the Fourier transform of f(x) as

[tex]
F(K) = \frac{1}{\sqrt{2\pi}} \int\limits_{-\infty}^\infty f(x) e^{-ikx} dx
[/tex]

Likewise for g(x) I have

[tex]
G(K) = \frac{1}{\sqrt{2\pi}} \int\limits_{-\infty}^\infty g(x) e^{-ikx} dx
[/tex]

for F(K/lambda) I have

[tex]
F(K/\lambda) = \frac{1}{\sqrt{2\pi}} \int\limits_{-\infty}^\infty f(\lambda x + y) e^{-ik(\lambda x + y)/\lambda} d(\lambda x + y)
[/tex]

My guess is that the answer is relatively simple from here, but I'm not sure how to go about it. Does anyone understand this?
 
Last edited:
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  • #2
dimensionless said:
Here's my problem:


I've got the Fourier transform of f(x) as

[tex]
F(K) = \frac{1}{\sqrt{2\pi}} \int\limits_{-\infty}^\infty f(x) e^{-ikx} dx
[/tex]

Likewise for g(x) I have

[tex]
G(K) = \frac{1}{\sqrt{2\pi}} \int\limits_{-\infty}^\infty g(x) e^{-ikx} dx
[/tex]

for F(K/lambda) I have

[tex]
F(K/\lambda) = \frac{1}{\sqrt{2\pi}} \int\limits_{-\infty}^\infty f(\lambda x + y) e^{-ik(\lambda x + y)/\lambda} d(\lambda x + y)
[/tex]
You should simply apply the defintion to g(x), so

[tex] G(k) = {1 \over {\sqrt{ 2 \pi}} } \int dx \,f(\lambda x + y) \, e^{-i kx} [/tex]

Now, define a new variable x'= lambda x + y so that x=(x'-y)/lambda and dx= dx'/lambda.

You get

[tex] G(k) = { 1\over \lambda} {1 \over {\sqrt{ 2 \pi}}} \int \, dx' \, f(x') \, e^{-i k x'/ \lambda} e^{i k y / \lambda} [/tex]

which directly gives the result you were looking for (I am asusming there was typo in the fomula you gave and that the y was missing in the exponent).

Patrick
 

1. What is the Fourier Transform and how is it used to solve problems?

The Fourier Transform is a mathematical operation that decomposes a function into its frequency components. It is commonly used in signal processing and image analysis to convert a signal from its original domain (such as time or space) to a representation in the frequency domain. This allows for easier analysis and manipulation of the signal.

2. What are some common issues that can arise when using the Fourier Transform?

One common issue is known as spectral leakage, which occurs when there are discontinuities or sharp edges in the signal being transformed. This can result in inaccurate frequency components and distort the original signal. Another issue is aliasing, which can occur when the sampling rate is too low and high frequency components are misrepresented as lower frequencies.

3. How can the problem of spectral leakage be addressed?

Spectral leakage can be reduced by using a window function, which applies a weighting to the signal before it is transformed. This helps to smooth out sharp edges and reduce the impact of discontinuities. Other techniques, such as zero-padding or using a higher sampling rate, can also help to mitigate the effects of spectral leakage.

4. What is the relationship between the Fourier Transform and the Inverse Fourier Transform?

The Fourier Transform converts a signal from the time domain to the frequency domain, while the Inverse Fourier Transform does the opposite - it converts a signal from the frequency domain back to the time domain. Together, they allow for the analysis and manipulation of signals in both domains.

5. How is the Fast Fourier Transform (FFT) different from the traditional Fourier Transform?

The Fast Fourier Transform is a more efficient algorithm for calculating the Fourier Transform. It takes advantage of symmetries and patterns in the signal to reduce the number of computations required. This makes it much faster than the traditional Fourier Transform, especially for larger signals with many frequency components.

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