Recovering a function using the inverse fourier transform

In summary, the argument of the kernel of the Fourier transform can have different signs for the forward and inverse transform. This means that for a general function, the original function cannot be fully recovered upon inverse transformation if the sign of the argument is the same for both transforms. One method for attempting to recover the original function involves integrating the exponent part of the inverse Fourier transform formula, but this method is not accurate as it approaches the delta function as the variable approaches infinity. A more accurate solution can be found by plugging in the expression for F(ω) into the inverse Fourier transform integral.
  • #1
hahashahid
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Homework Statement


The argument of the kernel of the Fourier transform has a different sign for the forward and inverse transform. For a general function, show how the original function isn’t recovered upon inverse transformation if the sign of the argument is the same for both the forward and inverse transform.


Homework Equations


The Fourier and the Inverse Fourier transform integrals


The Attempt at a Solution


Do I need to prove the inverse Fourier theorem or is there a simpler solution?
One attempt that I have seen at recovering the original function using the inverse Fourier transform formula integrates the exponent part to a sin(Mx)/x type function, which is then shown to approach the delta function as M approaches ∞.
 
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  • #2
Let
$$F(\omega) = \frac{1}{\sqrt{2\pi}}\int_{-\infty}^\infty f(t)e^{-i\omega t}\,dt.$$ The problem is simply asking you to show that if you calculate
$$\frac{1}{\sqrt{2\pi}}\int_{-\infty}^\infty F(\omega)e^{-i\omega t}\,d\omega,$$ you do not recover f(t). Just plug the expression for F(ω) into the second integral and calculate away.
 

1. What is the inverse Fourier transform?

The inverse Fourier transform is a mathematical operation that takes a function in the frequency domain and converts it back to its original form in the time domain. It essentially "undoes" the Fourier transform, which is a common technique used in signal processing and data analysis.

2. How is the inverse Fourier transform calculated?

The inverse Fourier transform is typically calculated using an integral formula, which involves integrating the complex conjugate of the function in the frequency domain over all possible frequencies. This integral can be solved using various numerical methods, such as the Fast Fourier Transform (FFT) algorithm.

3. What is the purpose of using the inverse Fourier transform?

The inverse Fourier transform is commonly used to recover a function or signal in the time domain from its representation in the frequency domain. This allows for easier analysis and manipulation of the data, as well as identifying specific frequencies or patterns within the signal.

4. What types of functions can be recovered using the inverse Fourier transform?

The inverse Fourier transform can be applied to a wide range of functions, including continuous, discrete, and even periodic functions. It is commonly used in fields such as physics, engineering, and mathematics to analyze signals and systems.

5. Are there any limitations to using the inverse Fourier transform?

While the inverse Fourier transform is a powerful tool, it does have some limitations. For example, it assumes that the function is well-behaved and has a valid Fourier transform. It may also introduce errors or distortions in the recovered function if the original data is noisy or contains artifacts.

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