Understanding Fourier Series, Transform and DFT

In summary, the Fourier family of transforms includes the Fourier Series, Fourier Transform, and Discrete Fourier Transform. The Fourier Series is used for periodic continuous signals, while the Fourier Transform can be used for periodic or aperiodic signals. The Discrete Fourier Transform is always finite as it is used for sampled data. Some books may mention four versions in the family, including DFT and FFT, which are similar but the latter is faster.
  • #1
Jag1972
40
0
Hello All,
I am little confused with the Fourier family of transforms. I would really appreciate it if someone could have a look at them
My understanding is as follows:

Fourier Series: Only used for Peiodic continuous signals.

Fourier Transform: Can be used for periodic or aperiodic signals, I think. This transform to me seems
to look the same as the Fourier Series its just more compact as it uses Eulers formulae and embeds the average
into the 1 summation (n=0). If signal is aperiodic then is is just assummed to be periodic.

Discrete Fourier Transform: Always finite as data is bieng sampled.

In some of the books I am reading there are 4 versions in teh Fourier family, I don't quite know why.

Thank you in advance for taking the time to help in advance.

Jag.
 
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  • #2
Fourier Transform: Can be used for periodic or aperiodic signals, I think. This transform to me seems
to look the same as the Fourier Series its just more compact as it uses Eulers formulae and embeds the average
into the 1 summation (n=0). If signal is aperiodic then is is just assummed to be periodic.
The Fourier transform requires a continuous function as the input and its output is another continuous function (so the spectrum of the signal is NOT discrete). Unlike Fourier transform, Fourier serie gives a discrete spectrum, not a continuous one.
In some of the books I am reading there are 4 versions in teh Fourier family
Maybebecause there is DFT, Discrete Fourier Transform, and FFT, Fast Fourier Transform. They are similar, but the second one is faster.
 

Related to Understanding Fourier Series, Transform and DFT

1. What is a Fourier series and how is it used in science?

A Fourier series is a mathematical representation of a periodic function as a sum of sinusoidal functions. It is used in science to analyze and understand complex, periodic phenomena, such as sound and electromagnetic waves.

2. What is the difference between a Fourier transform and a Fourier series?

A Fourier transform is a mathematical operation that converts a function from its time or spatial domain to its frequency domain. It is used to analyze non-periodic functions, while a Fourier series is used for periodic functions.

3. How is the Discrete Fourier Transform (DFT) different from the Fourier Transform?

The Discrete Fourier Transform (DFT) is a discrete version of the Fourier Transform, used to analyze discrete, periodic signals. It is often used in digital signal processing and image processing, while the Fourier Transform is used for continuous signals.

4. What are the applications of Fourier series and transforms in real-world problems?

Fourier series and transforms have a wide range of applications in science and engineering, including signal processing, image and video compression, medical imaging, and solving differential equations.

5. Are there any limitations to using Fourier series and transforms in data analysis?

While Fourier series and transforms are powerful tools for analyzing periodic and non-periodic signals, they have some limitations. For example, they assume that the data is stationary and linear, which may not always be the case in real-world data. Additionally, they can produce artifacts in the frequency domain if the data is not properly pre-processed.

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