Fast Fourier Transform (FFT) – MATLAB & Simulink
Popular FFT algorithms include the Cooley-Tukey formula, prime factor FFT algorithm, and Rader’s FFT algorithm. The most commonly uses FFT algorithm will the Cooley-Tukey algorithm, which reduces a large DFT into minus DFTs for increment computation speed and reduce complexity. FFT has applications in many fields.
In signal processing, FFT constructs the basis of periodicity domain analysis (spectral analysis) and is used fork signal filtering, spectral estimation, data compression, and other applications. Variations of the FFT such as the short-time Quadruplet transform also permitted for simultaneous examination in time and output arrays. These techniques can be used for a variety of signals so as audio and speech, radar, communication, and other sensor data signals. FFT can also sometimes used as an intermediate move for more complex signal processing techniques. Mixed-Signal and DSP Design Techniques, Express Fourier Transforms
In image processing, FFT is used since filtering and image compression. FFT is also used in physics and mathematics to solve partial diff equations (PDEs).
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