FFT Problem Solved by Mathematica | Exercise 2

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In summary, Gazi is trying to solve a FFT problem using Mathematica, but is having difficulty understanding the algorithm. He is looking for help from others, but is unsure if he is capable of doing it himself. He is also concerned about his thesis project if he cannot solve the FFT problem.
  • #1
gazi habiba
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Hi,
I have to solve a FFT problem by mathematica.I have attached my problem(exercise 2) here. I do not understand fft algorithm well.I also try to solve it by mathematica but mathematica can not solve this by forier transform directly.It will be great if anyone help me to solve this problem.
 
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  • #2
Hi,
I have to solve a FFT problem by mathematica.I have attached my problem(exercise 2) here. I do not understand fft algorithm well.I also try to solve it by mathematica but mathematica can not solve this by Fourier transform directly.It will be great if anyone help me to solve this problem.
 
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  • #3
You do not need to understand FFT algorithm. You only need to understand relation betwen Discrete Fourier Transform (DFT) and Continuous Fourier Transform to understand how a numerical model using DFT approximates the analytic form with Fourier Transformed functions.

Once you understand that, you can simply use Mathematica's built in function to apply FFT to compute DFT of arrays you supply. Don't worry too much about HOW Mathematica does it. You just need to know what the results mean.

Edit: Just to clarify, DFT is a vector transformation. It's the set of rules on how to take a vector and produce a transformed vector. FFT is a specific numerical method for making this transformation really fast. It's a very interesting topic, but you usually don't need to know how it actually happens.
 
  • #4
Thanks for your reply.
I read some books for understand FFT and DFT.It is not clear to me still now.May be i am not math or physics student for that reason i cannot understand.I can not go forward my thesis without solving this. Is it possible to explain me with a simple function like f(t)= Exp[-t^2] instead of my function.

thanks,
Gazi
 
1.

What is the FFT problem and how is it solved by Mathematica?

The FFT (Fast Fourier Transform) problem is a mathematical algorithm used to convert a time-domain signal into its frequency-domain representation. It is commonly used in signal processing and data analysis. Mathematica is a powerful software program that can efficiently solve FFT problems by using advanced mathematical algorithms and built-in functions specifically designed for this purpose.

2.

What is the purpose of Exercise 2 in the FFT problem using Mathematica?

Exercise 2 is designed to help users gain a better understanding of how to use Mathematica to solve FFT problems. It provides a hands-on experience for users to practice and apply the concepts they have learned, such as using the correct syntax and parameters for the built-in functions, and interpreting the results.

3.

Can Mathematica solve FFT problems for any type of signal?

Yes, Mathematica can solve FFT problems for any type of signal, whether it is a simple sine wave or a complex signal with multiple frequencies and noise. However, the accuracy and efficiency of the solution may vary depending on the complexity of the signal and the parameters used.

4.

Do I need a strong background in mathematics to use Mathematica for solving FFT problems?

While having a background in mathematics may be helpful, it is not necessary to use Mathematica for solving FFT problems. The software has a user-friendly interface and provides built-in functions that make it accessible for users with various levels of mathematical knowledge. However, a basic understanding of signal processing and FFT principles is recommended.

5.

Are there any limitations to using Mathematica for solving FFT problems?

Like any software program, Mathematica has its limitations. While it can efficiently solve FFT problems, the accuracy and speed of the solution may be affected by factors such as the complexity of the signal, the parameters used, and the computer's processing power. It is always recommended to double-check the results and make necessary adjustments if needed.

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