There's no need for it.
FT is needed for spectrum analysis, FFT is fast FT meaning it is used to obtain spectrum of a signal quickly, the FFT algorithm inherently is fast algorithm than the conventional FT algorithm
because they have a high speed compared to fft
FFT reduces the computation since no. of complex multiplications required in FFT are N/2(log2N). FFT is used to compute discrete Fourier transform.
plot(abs(fft(vectorname)))the FFT function returns a complex vector thus when you plot it, you get a complex graph. If you plot the absolute value of the FFT array, you will get the magnitude of the FFT.
In MATLAB, the radix-4 Fast Fourier Transform (FFT) can be implemented using the fft function, which computes the FFT efficiently for power-of-two input sizes. For radix-4 specifically, you can manually implement the algorithm by recursively breaking down the FFT into smaller FFTs of size N/4. This involves reordering the input data and performing the necessary butterfly operations. However, it's often more efficient to simply use MATLAB's built-in fft function, which is optimized for various FFT lengths, including radix-4.
FFT is faster than DFT because no. of complex multiplication in DFT is N^2 while in FFT no. of complex multiplications are N/2(log2N). for example if N=8 no. of complex multiplications required in DFT are 64. while no. of complex multiplications required in FFT are 12 thus reduces computation time.
Fast Fourier Transform
Food For Thought
hi.... for DIT fft algorithm, refer to this link, it has c-code for that. http://cnx.org/content/m12016/latest/
A disadvantage of the Zoom FFT is that it can be computationally intensive, particularly for very high-resolution frequency analysis, as it may require multiple FFT computations to achieve the desired frequency precision. Additionally, it may introduce artifacts or reduce frequency resolution in regions outside the zoomed range, which can complicate the interpretation of results. Lastly, the need for careful parameter selection in the zooming process can make it less user-friendly for those unfamiliar with its intricacies.
1045
FFT is the frequency domain representation. In can be shown in Simulink with blocks. These blocks graphically show the domain or x value plotted against the frequency or y value.