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An N-point DFT is expressed as the multiplication =, where is the original input signal, is the N-by-N square DFT matrix, and is the DFT of the signal. The transformation matrix W {\displaystyle W} can be defined as W = ( ω j k N ) j , k = 0 , … , N − 1 {\displaystyle W=\left({\frac {\omega ^{jk}}{\sqrt {N}}}\right)_{j,k=0,\ldots ,N-1 ...
[A] [1] An inverse DFT (IDFT) is a Fourier series, using the DTFT samples as coefficients of complex sinusoids at the corresponding DTFT frequencies. It has the same sample-values as the original input sequence. The DFT is therefore said to be a frequency domain representation of the original input sequence. If the original sequence spans all ...
One can ask whether the DFT matrix is unitary over a finite field. If the matrix entries are over F q {\displaystyle F_{q}} , then one must ensure q {\displaystyle q} is a perfect square or extend to F q 2 {\displaystyle F_{q^{2}}} in order to define the order two automorphism x ↦ x q {\displaystyle x\mapsto x^{q}} .
Density functional theory (DFT) is a computational quantum mechanical modelling method used in physics, chemistry and materials science to investigate the electronic structure (or nuclear structure) (principally the ground state) of many-body systems, in particular atoms, molecules, and the condensed phases.
The split-radix FFT is a fast Fourier transform (FFT) algorithm for computing the discrete Fourier transform (DFT), and was first described in an initially little-appreciated paper by R. Yavne (1968) and subsequently rediscovered simultaneously by various authors in 1984.
The Cooley–Tukey algorithm, named after J. W. Cooley and John Tukey, is the most common fast Fourier transform (FFT) algorithm. It re-expresses the discrete Fourier transform (DFT) of an arbitrary composite size = in terms of N 1 smaller DFTs of sizes N 2, recursively, to reduce the computation time to O(N log N) for highly composite N (smooth numbers).
The discrete Fourier transform is defined by a specific Vandermonde matrix, the DFT matrix, where the are chosen to be n th roots of unity. The Fast Fourier transform computes the product of this matrix with a vector in O ( n log 2 n ) {\displaystyle O(n\log ^{2}n)} time.
A decimation-in-time radix-2 FFT breaks a length-N DFT into two length-N/2 DFTs followed by a combining stage consisting of many butterfly operations. More specifically, a radix-2 decimation-in-time FFT algorithm on n = 2 p inputs with respect to a primitive n -th root of unity ω n k = e − 2 π i k n {\displaystyle \omega _{n}^{k}=e^{-{\frac ...