Howtosignalprocessing
- Is the FFT of a real signal real?
- What is the difference between the DFT and FFT of a signal?
- Why FFT is used instead of DFT?
- What are the limitations of discrete Fourier transform?
Is the FFT of a real signal real?
Most real-world signals are real-valued. Therefore, you can use the real fast Fourier transform (FFT) for most applications. You also can use the complex FFT by setting the imaginary part of the signal to zero.
What is the difference between the DFT and FFT of a signal?
Discrete Fourier Transform (DFT) is the discrete version of the Fourier Transform (FT) that transforms a signal (or discrete sequence) from the time domain representation to its representation in the frequency domain. Whereas, Fast Fourier Transform (FFT) is any efficient algorithm for calculating the DFT.
Why FFT is used instead of DFT?
FFT algorithms are faster ways of doing DFT. It is a family of algorithms and not a single algorithm. How it becomes faster can be explained based on the heart of the algorithm: Divide And Conquer.
What are the limitations of discrete Fourier transform?
These signals can be represented as the sum of a random discrete signal and harmonics of various frequencies. In the Fourier analysis of mixed-structure signals, the disadvantages of DFT are most significantly manifested. These disadvantages are picket-fence, leakage, aliasing effects and amplitude modulation spectrum.
