Looking for Periodicity by Using the Fourier Transform

In summary, when taking the Fourier Transform of a function g(x) with an unknown period, the integral should have limits from negative infinity to positive infinity. This is different from the Fourier series, where the period is known and the integral has specific limits. If g(x) has a strong periodic component, it will be reflected in the Fourier transform as a spike at that frequency.
  • #1
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Homework Statement



One has a function g(x) that has a periodic nature, but the period is unknown (the term 'period' is used a bit loosely). To be specific, the g(x) (i.e. a signal) appears to oscillate, but the displacement between each oscillation is unknown (nothing is known about whether the period is varying or constant). g(x) is defined for all real numbers.

When taking the Fourier Transform of g(x), what would you put as the bounds for the integral itself?

Homework Equations



Also: g(x) 'somewhat' mirrors the function xsin(x), incase that's of importance.

The Attempt at a Solution



I'm guessing you cannot put an actual period value (as you do not know it), nor can you put Lower Bound: -T/2, Upper Bound: T/2 and let the period stretch to infinity, because the signal does appear to oscillate and appears to be loosely periodic. Other then these two methods, I'm not familiar with how to define the bounds of the Fourier Transform of g(x).

I've been stuck on this problem for a while, and I can't seem to get past that one thing. Any help would be greatly appreciated.
 
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  • #2
You're mixing up the Fourier series with the Fourier transform. The integral for the transform has limits from [itex]-\infty[/itex] to [itex]+\infty[/itex]. If there is a strong periodic component in g(x), you'll see a spike in the Fourier transform's amplitude at that frequency.
 

Related to Looking for Periodicity by Using the Fourier Transform

1. What is the Fourier Transform and how does it relate to periodicity?

The Fourier Transform is a mathematical tool used to decompose a function into its individual frequency components. It is useful for identifying periodicity because periodic functions have distinct frequency components that can be easily identified using the Fourier Transform.

2. Can the Fourier Transform be used to analyze any type of signal?

Yes, the Fourier Transform can be used to analyze any signal as long as it is represented as a continuous function. This includes signals in the time, frequency, or spatial domains.

3. How can the Fourier Transform be used to detect periodicity in a signal?

The Fourier Transform can be used to identify the dominant frequency components in a signal. If a signal is periodic, there will be distinct peaks in the frequency spectrum at regular intervals, indicating the presence of periodicity.

4. Are there any limitations to using the Fourier Transform for detecting periodicity?

Yes, the Fourier Transform assumes that the signal being analyzed is infinite and continuous. This can be problematic for signals that are only observed for a finite period of time or have discontinuities.

5. Are there any alternative methods for detecting periodicity besides the Fourier Transform?

Yes, there are other methods such as autocorrelation and wavelet analysis that can also be used to detect periodicity in a signal. These methods may be more suitable for signals with finite or non-continuous components.

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