Memory requirements for FFT

The memory requirement, for a 2*N point Real to Complex FFT, is only 2*N Complex memory locations broken into 4 banks. Both DIF and DIT FFT modes are used, altemately, (FFT-mode mixing).

1. How many points do you need for FFT?
2. What is 64 point FFT?
3. How much faster is FFT than DFT?
4. What is the need of FFT?

How many points do you need for FFT?

Because the FFT function uses a base 2 logarithm by definition, it requires that the range or length of the time series to be evaluated contains a total number of data points precisely equal to a 2-to-the-nth-power number (e.g., 512, 1024, 2048, etc.).

What is 64 point FFT?

The 64-point FFT is realized by decomposing it into a two-dimensional structure of 8-point FFTs. This approach reduces the number of required complex multiplications compared to the conventional radix-2 64-point FFT algorithm. The complex multiplication operations are realized using shift-and-add operations.

How much faster is FFT than DFT?

Graphical explanation for the speed of the Fast Fourier Transform. For a sample set of 1024 values, the FFT is 102.4 times faster than the discrete Fourier transform (DFT). The basis for this remarkable speed advantage is the `bit-reversal' scheme of the Cooley-Tukey algorithm.

What is the need of FFT?

The FFT algorithm is heavily used in many DSP applications. It is used whenever the signal needs to be processed in the spectral or frequency domain. Because it is so efficient to implement, sometimes even FIR filtering functions are performed using an FFT.