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.
To plot the frequency spectrum using the fft function in MATLAB, first compute the one-dimensional discrete Fourier transform using fft, provide the data series as an input. Then use the abs() function to get the magnitude spectrum, and plot the result using the plot() function, with the frequency domain on the x-axis and the magnitude spectrum on the y-axis.
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.
Food For Thought
Fast Fourier Transform
hi.... for DIT fft algorithm, refer to this link, it has c-code for that. http://cnx.org/content/m12016/latest/
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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.
A Discrete Fourier Transform is simply the name given to the Fourier Transform when it is applied to digital (discrete) rather than an analog (continuous) signal. An FFT (Fast Fourier Transform) is a faster version of the DFT that can be applied when the number of samples in the signal is a power of two. An FFT computation takes approximately N * log2(N) operations, whereas a DFT takes approximately N^2 operations, so the FFT is significantly faster simple answer is FFT = Fast DFT
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