Fast Fourier Transform (FFT) is an efficient algorithm to compute the discrete Fourier Transform (DFT) and its inverse in computational effective way. It reduces the number of computations required to compute N point DFT from 2 N^2 to 2N log N. Therefore the ratio between a DFT computation and an FFT computation for the same N is proportional to N/log(2) N. It takes time domain input data and converts into frequency spectral domain data, which would be used for spectral analysis and which contains most of the signal information for signal processing applications.
The FFT has many applications, all digital signal processing applications. In fact any field of that uses sinusoidal signals will make use of FFT. Some of the areas are in Communications, Astronomy, Geology and Optics.
- 1. Configurable for N point data
- 2. Uses Radix-2, 4, 8 FFT for decimation in time
- 3. Inverse FFT is integrated
- 4. Optimal area implementation
- 5. Can handle real and imaginary data.
- 6. Uses Fixed point implementation.
- 1. Encrypted RTL source code
- 2. Test benches
- 3. Synthesis and Simulation scripts
- 4. Detailed user documentation,