What are the limitations/ disadvantages of the Fourier Tran

In summary, the Fourier transform is a powerful tool that can be used for a variety of tasks, but there are limitations to its use that need to be taken into account.
  • #1
ramdas
79
0
I am fond of Fourier series &
Fourier transform. In Fourier
domain, we can come to know
what frequency components are
present and the contribution of
each component in forming the
given signal.But every approach has some
advantages and
disadvantages.Here, I want to
know what are the limitations/
disadvantages of the Fourier
Transform and Fourier Series? It
would be better for me if you
explain them with the help of
example(or links or any relevant
information) to understand
them easily.
 
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  • #2
Well, if you have a time domain function and you need a position domain function, the Fourier transform is unlikely to be a lot of help.
i.e. it is no good in any situation where you don't need the Fourier transform.

Tools are useful in their contexts - and most limitations for a tool in context are not about the context. i.e. a hammer is good for hammering nails, but it can be slow and tiring, especially if you want to attach wood to concrete, so ramset. But that is not a limit of the hammer, it is a limit of the user and the job (time constraint not inherent to hammer).

So to understand the limits of the Fourier transform - whose usefulness is not limited to just finding the frequency domain function from a time domain function - you need to understand the types of jobs you may want it to do and what sorts of constraints those jobs have to work under. i.e. numerical analysis of a discrete time-series as a real-time inverse problem.
 
  • #3
If the original data is already discrete and finite, then there is no loss of information when doing a discrete Fourier transform. It is therefore just a different way to look at the same information content, and as Simon said, whether to look at something in time (or position) or in frequency it's a matter of what you are trying to accomplish.
 
  • #4
Why my question is deleted.If it is duplicate ,where is the original one?
 
  • #5
ramdas said:
Why my question is deleted.If it is duplicate ,where is the original one?

This is the original thread. I deleted the duplicate thread last night. If you have any questions about this, please message me.
 

Related to What are the limitations/ disadvantages of the Fourier Tran

What are the limitations/ disadvantages of the Fourier Transform?

The Fourier Transform is a powerful mathematical tool used in many fields of science and engineering. However, like any tool, it has its limitations and disadvantages. Here are five frequently asked questions about the limitations of the Fourier Transform and their answers:

1. Can the Fourier Transform handle complex signals?

The Fourier Transform can only handle signals that are time-invariant and periodic. This means that it cannot accurately represent signals that are non-periodic or that change over time. Complex signals, such as those with discontinuities or sharp spikes, can be difficult to accurately represent with the Fourier Transform.

2. Does the Fourier Transform work for all types of data?

The Fourier Transform is best suited for analyzing and processing continuous data. It is not well suited for discrete data, as it assumes a continuous signal. Additionally, the Fourier Transform can only be applied to signals that are stationary, meaning that their statistical properties do not change over time.

3. Are there limitations to the resolution of the Fourier Transform?

The Fourier Transform has a limited frequency resolution, meaning that it can only accurately detect and measure frequencies that are integer multiples of its sampling frequency. This can be a limitation when working with signals that have very high or very low frequencies.

4. Can the Fourier Transform handle signals with noise?

The Fourier Transform is highly sensitive to noise in the signal. Even a small amount of noise can significantly affect the accuracy of the transformed signal. This can be a disadvantage when working with real-world data that is often noisy.

5. What are the limitations of using the Fourier Transform for non-linear systems?

The Fourier Transform assumes that the system being analyzed is linear, meaning that the output is directly proportional to the input. However, many real-world systems are non-linear, and the Fourier Transform is not suitable for analyzing these types of systems. In these cases, other methods, such as the Fast Fourier Transform, may be more appropriate.

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