Why is Fourier Integral Meaningless for f(x)=A*cos(ax)?

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SUMMARY

The Fourier integral is deemed meaningless for the function f(x) = A*cos(ax) because the absolute value |f(x)| is not integrable over the entire real line, thus preventing a proper definition of the Fourier integral. The discussion highlights the importance of square integrability and suggests using the Delta function for analysis. Prof. Brad Osgood's lectures on Fourier transforms, particularly those covering distributions and Schwartz functions, provide valuable insights into this topic. Additionally, the conversation touches on the application of Fast Fourier Transform (FFT) in MATLAB for non-uniform sampling, raising questions about the validity of the results obtained.

PREREQUISITES
  • Understanding of Fourier integrals and transforms
  • Knowledge of square integrability and Delta functions
  • Familiarity with distributions and Schwartz functions
  • Basic proficiency in MATLAB and Fast Fourier Transform (FFT) techniques
NEXT STEPS
  • Study Prof. Brad Osgood's lectures on Fourier transforms available on iTunesU
  • Read chapter 4 of the Stanford EE261 lecture notes on distributions
  • Explore the mathematical foundations of square integrability in Fourier analysis
  • Investigate the application of FFT on non-uniform sampling in MATLAB
USEFUL FOR

Mathematicians, physicists, engineers, and computer scientists interested in Fourier analysis, signal processing, and the application of FFT in non-uniform sampling scenarios.

caduceus
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I couldn't understand that why the Fourier integral is meaningless for f(x)=A*cos(ax) ?

Any comments will be appreciated.
 
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|f(x)| is not integrable over (-oo,oo). so the Fourier integral cannot be properly defined.
 
caduceus said:
I couldn't understand that why the Fourier integral is meaningless for f(x)=A*cos(ax) ?

Any comments will be appreciated.

Because that is a sinusoidal function. What is there to analyze?

You want to find the sinusoidal functions that make up a non sinusoidal function.
 
Oh, I guess I can see the point now. You mean square integrability. That is why I should use Delta function. Thank you.
 
Prof Brad Osgood has some excellent Fourier transform lectures on iTunesU
(The Fourier Transform and its Applications).

In particular, there's a few lectures (~lectures 10-14 I think) on distributions and Schwartz functions that help show how Fourier transforms of sines, exponentials, deltas, ... can be better justified. Suprisingly (to me after having seen and given up trying to understand Functional analysis), the basics required for application are not actually all that difficult, mostly requiring a change in approach, and an extra level of indirection.

Some lecture notes to go with the lectures can be found here:

http://www.stanford.edu/class/ee261/book/all.pdf

(chapter 4 covers distributions).
 
Last edited by a moderator:
caduceus said:
I couldn't understand that why the Fourier integral is meaningless for f(x)=A*cos(ax) ?

Any comments will be appreciated.
The Fourier integral gives two delta functions. That is good enough for physicists.
 
well i am a computer guy :) so i don't know...ok here is my question
following are two equations


$fk(k1) = \frac{1}{nj} \sum_{j=1}^{nj} c_j(j) \exp (i k1 x_j(j))$\\

$where \frac {-ms}{2} <k1 < \frac{ms-1}{2}$

a) what is k1
b) what is x_j(j)
c) what is c_j(j)

Is this a forward transform

d) What will be the inverse transform, and is inverse tranform means we are evaluating Fourier series
 
that's not really readable as is. Can you edit with [ tex ] [ / tex ] (no spaces), replacing the dollar signs.
 
I am experimenting with non uniform sampling, I applied Fast Fourier transform on the non uniform sampling in MATLAB it has given me some results. I can't understand how FFT runs on non uniform sampling. What i am getting after applying FFT on Non uniform samples is what...is it a errorfull value if yes then why
 

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