Fourier Transform question

In summary, the conversation discusses the use of Fourier transform to distinguish between clockwise and counterclockwise rotating vectors. It also addresses the presence of both positive and negative frequencies in real-valued signals and the use of an integral of cos(wt) f(t) to calculate Fourier transforms. The conversation also mentions the use of a delta function and the realization that only multiplying by coswt is needed to calculate the Fourier transform in certain cases.
  • #1
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Why can't Fourier transform distinguish between a clockwise and a counter clockwise rotating vector? Why does it give peaks at both + and -.
If we discard the -ve frequency and use only the +ve frequency, we can just use
[tex]\int[/tex] f(t)coswt instead of {f(t)(coswt-isinwt)}
 
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  • #2
What do you mean by "rotating vector"? Do you mean a complex-valued function whose phase angle rotates with time, or do you really mean a vector and some kind of multi-dimensional Fourier transform?

Fourier transforms certainly do distinguish between functions with phases that rotate in different directions! I don't know why you think they don't.

I'm also not sure what you mean by "peaks at + and -". Are you just asking why a real-valued signal has both positive and negative frequency components? That's because the positive and negative frequencies represent complex-valued functions that spiral in opposite directions, and they add together to produce a real-valued function.

I feel like I'm not answering your question. Can you try to explain a little more clearly?
 
  • #3
Oh, one other thing: you mention trying to use an integral of cos(wt) f(t). That won't work because it assumes that the phase of every frequency component is zero. Not all signals have this property. For example, no matter how many cosines you add together, the value at time t=0 will just keep getting bigger and bigger, because all cosines have a value of 1 at t=0.
 
  • #4
Xezlec, I was reading this FT tutorial here - http://www.cis.rit.edu/htbooks/nmr/inside.htm
By 'rotating vector' , I meant complex-valued function whose phase angle rotates with time.
By + and - peaks, I did mean positive and negative frequencies.
I was trying to calculate the FT of a delta function by multiplying the delta function by (coswt-isinwt) for different w and then adding up.
It works for a function like cos 4t+cos9t (as in the link above). I had never thought of FT in this way. Me so dumb. For this example, it is enough to multiply only by coswt. No need for isinwt.
 

What is a Fourier Transform?

A Fourier Transform is a mathematical tool that allows us to break down a signal or function into its individual frequency components. It converts a signal from its original domain (such as time or space) to a representation in the frequency domain.

Why is the Fourier Transform important?

The Fourier Transform is important because it allows us to analyze and understand complex signals and functions by breaking them down into simpler components. This has applications in various fields such as signal processing, image processing, audio engineering, and physics.

How is the Fourier Transform calculated?

The Fourier Transform is calculated by integrating the signal or function multiplied by a complex exponential function over the entire domain. This can be done analytically or numerically using various algorithms.

What is the difference between Fourier Transform and Fourier Series?

The Fourier Transform is used for continuous signals or functions, while the Fourier Series is used for periodic signals or functions. The Fourier Transform gives us a continuous representation in the frequency domain, while the Fourier Series gives us a discrete representation with only the frequencies present in the periodic signal.

What is the inverse Fourier Transform?

The inverse Fourier Transform is the reverse process of the Fourier Transform. It converts a signal or function from the frequency domain back to its original domain. It allows us to reconstruct the signal or function using its frequency components.

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