What is the purpose/significance of doing a FFT on a signal?

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In summary, the FFT decompresses data by finding the frequencies of the data and then reducing the data to those frequencies. This is useful for image and sound compression, as well as for analyzing experimental data.
  • #1
zheng89120
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it seems like a pretty commonly used computational/mathematical method in analyzing experimental data, such as voltage signals
 
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  • #2
it is used to figure out what a signal consists of...you know, by decomposing it into a bunch of sinusoidal of various amplitudes and frequencies.
 
  • #3
FFT is just a computer algorithm to efficiently compute discrete Fourier transformation - represent given signal of weird shape as a sum of sinusoidal ones.
Most of electronic systems are:
1. linear - they response to sum of signals is equal to sum of responses to individual ones;
2. they response to sinusoidal stimulation is also a sinusoid of the same frequency (just amplitude is changed and phase shifted) - easy to analyse theoretically

So if you want to analyse its behaviour, you may first decompose your input signal as a sum of sinusoidal signals, compute the system response to every one of them, then sum the resulting sinusoidal signals again.

The same approach may apply not only to electronics, but also to many other fields - e.g. vibrations of mechanical systems, acoustics, etc.
 
  • #4
zheng89120 said:
it seems like a pretty commonly used computational/mathematical method in analyzing experimental data, such as voltage signals
1. It shows you the frequency spectrum. Like the one on Cisco logo :)
2. If you are looking for weak periodic signals among the noise, they will show up as spikes on frequency plot. Also it's easy to suppress unwanted periodic signals interfering with data.
3. Many common operations are much easier in frequency domain, correlation being prime example.
etc. etc.

DK
 
  • #5
It's also very useful in data compression, particularly if your analogue signal is very nearly a sinusoid anyway. A whole time series (lots of data) can be compressed to a very small number of amplitudes in the frequency domain. I'm pretty sure the FFT is used in most image/sound compression algorithms.
 

Related to What is the purpose/significance of doing a FFT on a signal?

1. What is a FFT and why is it used?

A FFT (Fast Fourier Transform) is a mathematical algorithm that is used to convert a signal from its original time domain into its frequency domain. This allows us to analyze the different frequencies present in a signal and understand its underlying patterns and characteristics. It is commonly used in signal processing, image processing, and other scientific fields.

2. How does a FFT work?

A FFT works by breaking down a signal into its individual frequency components using a series of mathematical operations. It uses the principle of decomposition to separate the signal into its constituent sinusoidal components. These components are then analyzed to determine the amplitude, frequency, and phase of each signal component.

3. What are the benefits of using a FFT?

There are several benefits to using a FFT. It allows us to analyze the frequency content of a signal, which can be useful in identifying patterns or anomalies. It is also computationally efficient, allowing us to process large amounts of data quickly. Additionally, it is a non-invasive technique, meaning it does not alter the original signal in any way.

4. What types of signals can be analyzed using a FFT?

A FFT can be used to analyze any signal that can be represented as a series of data points. This includes audio signals, images, and even non-physical signals such as financial data or weather patterns. However, the signal must be periodic in nature to accurately analyze its frequency components.

5. Are there any limitations to using a FFT?

While a FFT is a powerful tool for analyzing signals, it does have some limitations. It can only be used on signals that are periodic and have a finite length. It also assumes that the signal is stationary, meaning it does not change over time. Additionally, a FFT may not be suitable for analyzing signals with complex or non-linear frequency components.

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