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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 ...
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}} .
[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 ...
The exponential form of Fourier series is given by: = = [],which is periodic with an arbitrary period denoted by . When continuous time is replaced by discrete time , for integer values of and time interval , the series becomes:
The base cases of the recursion are N=1, where the DFT is just a copy =, and N=2, where the DFT is an addition = + and a subtraction =. These considerations result in a count: 4 N log 2 N − 6 N + 8 {\displaystyle 4N\log _{2}N-6N+8} real additions and multiplications, for N >1 a power of two.
Both transforms are invertible. The inverse DTFT reconstructs the original sampled data sequence, while the inverse DFT produces a periodic summation of the original sequence. The Fast Fourier Transform (FFT) is an algorithm for computing one cycle of the DFT, and its inverse produces one cycle of the inverse DFT.
In applied mathematics, the non-uniform discrete Fourier transform (NUDFT or NDFT) of a signal is a type of Fourier transform, related to a discrete Fourier transform or discrete-time Fourier transform, but in which the input signal is not sampled at equally spaced points or frequencies (or both).
The Goertzel algorithm is a technique in digital signal processing (DSP) for efficient evaluation of the individual terms of the discrete Fourier transform (DFT). It is useful in certain practical applications, such as recognition of dual-tone multi-frequency signaling (DTMF) tones produced by the push buttons of the keypad of a traditional analog telephone.