Gibbs Phenomenon: Impact on kth Harmonics for Bandwidth Selection

In summary, the Gibbs phenomenon increases the oscillations in a waveform as the number of harmonics increases. However, by using truncated Fourier series, or "windowing," the ringing artifacts can be reduced.
  • #1
goldfronts1
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How does the Gibbs Phenomenon effect the choice of the kth harmonics for bandwidth selection?

Basically, I have plotted a square wave using the Fourier series analysis for choosing the kth harmonics. As, I increase the kth harmonics the oscillations increase. What is the smallest harmonic i can go to that is still an accurate representation of the signal. Or does it not matter.

Confused

Thanks
 
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  • #2
As the number of harmonics (N) increases the resultant waveform becomes progressively closer (in the sense of mean square difference) to the original square wave. Gibbs phenomenon refers to the fact that, despite getting ever closer in a mean squared sense, the convergence is very poor near the discontinuity (the edge) and in fact the maximum error at the "ringing overshoot" doesn't actually get any smaller as you increase N.

Tapering (instead of abruptly truncating) the truncated Fourier series (also called "windowing") is a very useful method for reducing these ringing artefacts. For example you could taper off the series with a "Hamming" type of window using something like : [itex]w(k) = 0.54 + 0.46 \cos( (k-1)\pi/(N-1) )[/itex]

In other words, instead of using [itex]\sin(2 \pi (2k-1) t)/(2k-1)[/itex] for the k-th term in the series you would use [itex]w(k) \sin(2 \pi (2k-1) t)/(2k-1)[/itex] instead. Give it a try, you'll be surprised what a big improvement it makes.
 
  • #3
The attachment shows a 20 term (sine) Fourier series for a square wave, both with and without windowing being used. The window I used was w(k) as defined in the previous post.
 

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  • #4
Ok, so what's the difference if I use 60 terms, which gives me about 99% of the power in the signal versus using 20 terms which gives me about 95% of the power in the signal? When the ultimate goal is to have the smallest bandwidth. I guess the gibbs phenomenon is still present in either case, but the signal is closer to the original when you use more k-terms, but that uses up more bandwidth. Is this just a judgment call? I guess which one is best?
 
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1. What is Gibbs Phenomenon and how does it impact kth harmonics?

Gibbs Phenomenon refers to the overshoot of a signal at a discontinuity, causing a ringing effect. When applied to kth harmonics, this means that the harmonic components of a signal will also experience this overshoot at discontinuities, leading to distorted and inaccurate representations of the signal.

2. How does Gibbs Phenomenon affect bandwidth selection?

Gibbs Phenomenon can affect bandwidth selection by causing a trade-off between accuracy and smoothness. Choosing a smaller bandwidth may reduce the ringing effect, but it may also result in a loss of important harmonic information. On the other hand, choosing a larger bandwidth may lead to a smoother signal, but at the cost of increased distortion due to the overshoot of kth harmonics.

3. Is Gibbs Phenomenon always present in signals?

Yes, Gibbs Phenomenon is a fundamental property of Fourier analysis and is present in all signals with discontinuities. However, the severity of its impact may vary depending on the specific signal and its bandwidth selection.

4. How can Gibbs Phenomenon be mitigated?

There are several methods for mitigating Gibbs Phenomenon, such as windowing, filtering, and using non-uniform sampling techniques. These methods can reduce the ringing effect and improve the accuracy of kth harmonics, but they may also introduce other limitations and trade-offs.

5. What are the implications of Gibbs Phenomenon in practical applications?

Gibbs Phenomenon can have significant implications in practical applications, particularly in signal processing and data analysis. It can lead to inaccuracies in measurements and distortions in signal representations, which can affect the reliability and validity of results. Therefore, it is important for scientists and engineers to be aware of Gibbs Phenomenon and its impact in their respective fields.

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