Fourier Transform: Nonperiodic vs Periodic Signals

In summary, the Fourier transform is a continuous form of Fourier series, where the signal in time domain must be periodic and have a finite period. However, for nonperiodic signals, the Fourier transform can be applied to any integrable function. This allows for a continuous spectrum, as opposed to the discrete spectrum seen in Fourier series. The use of the term non-periodic is to generalize the applicability of the Fourier transformation. The decaying exponential is an example of a nonperiodic signal that can be transformed using the Fourier transform. However, its Fourier transform does not involve deltas and is not of finite length, leading to the question of how to attach a Fourier transform to such signals. It is possible that there are other derivations of
  • #1
RaduAndrei
114
1
In a book the Fourier transform is defined like this. Let g(t) be a nonperiodic deterministic signal... and then the integrals are presented.

So, I understand that the signal must be deterministic and not random. But why it has to be nonperiodic (aperiodic).
The sin function is periodic and we can calculate its Fourier transform.

Is it because a nonperiodic signal is absolutely integrable?

And with the sin function. Yes, I can calculate. But deltas appear.

This is the answer?
 
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  • #2
Fourier transform is a continuous form of Fourier series. In computing Fourier series, the signal in time domain must be periodic, i.e.it has finite period, and that you find that the spectrum contains combs separated by a fixed value which is reciprocal to the signal's period. So, the longer the period, the closer the frequency combs are to its neighbors. When the signal is not periodic, we can suppose that its period is infinitely long, therefore the corresponding frequency combs is separated by infinitesimal distance, which leads to a continuous spectrum.
 
  • #3
Ok.

But in computing the Fourier transform of a signal, that signal must be absolutely necessary nonperiodic?
 
  • #4
The use of the term non-periodic generalize the applicability of Fourier transformation to any integrable functions, be it periodic or non-periodic.
 
  • #5
Aa, ok. Thanks for the answer.

I think this is a problem with today's books. They are not written in a more Euclidean way.
 
  • #6
Also. When deriving the Fourier transform from the Fourier series, we have a finite-length signal and repeat it multiple times over the time axis. And then expand it into a Fourier series. And then calculations. And then we get the Fourier transform.

So the Fourier transform is for finite-length signals.

The fact that we can calculate Fourier transforms for periodic signals or signals like the unit step is because we involve deltas functions there.

But what about the decaying exponential? Its Fourier transform does not involve deltas and it is not of finite length.
How can this decaying exponential be viewed as a finite-length signal that gets repeated multiple times over the time axis. Its period is infinite.

So my question. How does one attach a Fourier transform to such decaying exponential? It could be the fact that for such signals we actually have other derivation of the Fourier transform but we haven't found it yet?
We derived the Fourier transform for finite-length signals and with it we just calculated the Fourier transform for decaying exponential?
Or one can think of having multiple infinities into one infinite. So we have that notion that some infinities are bigger than others?
 

1. What is the Fourier Transform?

The Fourier Transform is a mathematical tool used to decompose a signal into its constituent frequencies. It converts a time-domain signal into a frequency-domain signal, allowing us to better understand the frequency components of a signal.

2. What is the difference between a periodic and nonperiodic signal?

A periodic signal repeats itself at regular intervals, while a nonperiodic signal does not have a repeating pattern. This means that a periodic signal can be represented by a finite number of sine and cosine waves, while a nonperiodic signal requires an infinite number of waves for its representation.

3. How does the Fourier Transform handle periodic and nonperiodic signals differently?

The Fourier Transform of a periodic signal results in a discrete spectrum with peaks at the frequencies of the periodic components, while the Fourier Transform of a nonperiodic signal results in a continuous spectrum with no distinct peaks.

4. Can a nonperiodic signal be represented by a Fourier series?

No, a nonperiodic signal cannot be represented by a Fourier series because it does not have a repeating pattern. The Fourier series is only applicable to periodic signals.

5. What are some real-world applications of Fourier Transform for periodic and nonperiodic signals?

The Fourier Transform is widely used in many fields, including telecommunications, audio and image processing, and signal analysis. It is used to filter out noise, compress data, and extract useful information from signals. For periodic signals, the Fourier series is used to analyze and design electronic circuits, while the Fourier Transform is used for nonperiodic signals in fields such as medical imaging and geophysics.

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