Inverse fast Fourier transform
y = ifft(X)
y = ifft(X,n)
y = ifft(X,,dim)
y = ifft(X,n,dim)
y = ifft(..., 'symmetric')
y = ifft(..., 'nonsymmetric')
y = ifft(X) returns the inverse discrete Fourier transform (DFT) of vector X, computed with a fast Fourier transform (FFT) algorithm. If X is a matrix, ifft returns the inverse DFT of each column of the matrix.
ifft tests X to see whether vectors in X along the active dimension are conjugate symmetric. If so, the computation is faster and the output is real. An N-element vector x is conjugate symmetric if x(i) = conj(x(mod(N-i+1,N)+1)) for each element of x.
If X is a multidimensional array, ifft operates on the first non-singleton dimension.
y = ifft(..., 'symmetric') causes ifft to treat X as conjugate symmetric along the active dimension. This option is useful when X is not exactly conjugate symmetric, merely because of round-off error.
For any X, ifft(fft(X)) equals X to within roundoff error.
ifft supports inputs of data types double and single. If you call ifft with the syntax y = ifft(X, ...), the output y has the same data type as the input X.
The algorithm for ifft(X) is the same as the algorithm for fft(X), except for a sign change and a scale factor of n = length(X). As for fft, the execution time for ifft depends on the length of the transform. It is fastest for powers of two. It is almost as fast for lengths that have only small prime factors. It is typically several times slower for lengths that are prime or which have large prime factors.
Note You might be able to increase the speed of ifft using the utility function fftw, which controls how MATLAB® software optimizes the algorithm used to compute an FFT of a particular size and dimension.