Y = fft(X) computes the discrete Fourier transform (DFT) of X using a fast Fourier transform (FFT) algorithm. Y is the same size as X . If X is a vector, then fft(X) returns the Fourier transform of the vector.

Learn how to use fast Fourier transform (FFT) algorithms to compute the discrete Fourier transform (DFT) efficiently for applications such as signal and image processing. Resources include videos, examples, and documentation.

The fft function in MATLAB® uses a fast Fourier transform algorithm to compute the Fourier transform of data. Consider a sinusoidal signal x that is a function of time t with frequency components of 15 Hz and 20 Hz.

Y = fft2(X) returns the two-dimensional Fourier transform of a matrix X using a fast Fourier transform algorithm, which is equivalent to computing fft(fft(X).').'.

Y = fftn(X) returns the multidimensional Fourier transform of an N-D array using a fast Fourier transform algorithm. The N-D transform is equivalent to computing the 1-D transform along each dimension of X. The output Y is the same size as X.

The discrete Fourier transform, or DFT, is the primary tool of digital signal processing. The foundation of the product is the fast Fourier transform (FFT), a method for computing the DFT with reduced execution time.

The fft function uses a fast Fourier transform algorithm that reduces its computational cost compared to other direct implementations. For a more detailed introduction to Fourier analysis, see Fourier Transforms .

The discrete Fourier transform (DFT) transforms discrete time-domain signals into the frequency domain. The most efficient way to compute the DFT is using a fast Fourier transform (FFT) algorithm. This tech talk answers a few common questions …

The FFT Analyzer app allows you to perform Fourier analysis of simulation data and provides access to all the simulation data that are defined as structure-with-time variables in your workspace. The app displays the spectrum as a bar graph or as a list in percentages relative to a base value or to the DC component of the signal.

X = ifft(Y) computes the inverse discrete Fourier transform of Y using a fast Fourier transform algorithm. X is the same size as Y . If Y is a vector, then ifft(Y) returns the inverse transform of the vector.