What is Discrete fourier transform: Definition and 55 Discussions

In mathematics, the discrete Fourier transform (DFT) converts a finite sequence of equally-spaced samples of a function into a same-length sequence of equally-spaced samples of the discrete-time Fourier transform (DTFT), which is a complex-valued function of frequency. The interval at which the DTFT is sampled is the reciprocal of the duration of the input sequence. An inverse DFT 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 non-zero values of a function, its DTFT is continuous (and periodic), and the DFT provides discrete samples of one cycle. If the original sequence is one cycle of a periodic function, the DFT provides all the non-zero values of one DTFT cycle.
The DFT is the most important discrete transform, used to perform Fourier analysis in many practical applications. In digital signal processing, the function is any quantity or signal that varies over time, such as the pressure of a sound wave, a radio signal, or daily temperature readings, sampled over a finite time interval (often defined by a window function). In image processing, the samples can be the values of pixels along a row or column of a raster image. The DFT is also used to efficiently solve partial differential equations, and to perform other operations such as convolutions or multiplying large integers.
Since it deals with a finite amount of data, it can be implemented in computers by numerical algorithms or even dedicated hardware. These implementations usually employ efficient fast Fourier transform (FFT) algorithms; so much so that the terms "FFT" and "DFT" are often used interchangeably. Prior to its current usage, the "FFT" initialism may have also been used for the ambiguous term "finite Fourier transform".

View More On Wikipedia.org
  1. A

    How Do You Compute the DFT of Periodic Signals?

    Homework Statement Find the discrete Fourier transform X[k] = DFTn {x[n]} of the following periodic sequences x[n] = x[n - N] with period N: (a) For n = 0 . . .N - 1 we have x[n] =\delta[n]. (b) For n = 0 . . .N - 1 we have x[n] = \mu[n] -\mu[n - K] with K < N. (c) x[n] = cos( (2*pi*M*n)/N...
  2. T

    Matrix pseudo-inverse to do inverse discrete fourier transform

    Hello, can anyone help me with the following problem: The discrete Fourier transform (DFT) in matrix form can be done as follows F=M*f where f are the space domain samples, F are the spatial frequency domain samples and M is the DFT matrix containing the exp(j*...) terms. To compute the...
  3. E

    Inverse Discrete Fourier Transform proof help

    I'm reading the text Understanding Digital Signal Processing Second Edition and in the text they give the IDFT without any proof and so I tried to do a quick proof, but I have not been able do it here is my attempted steps: X(m)=\sum^{N-1}_{n=0}x(n)e^{-i2\pi mn/N} \\ Considering x(1)...
  4. hxtasy

    Sliding DFT discrete Fourier transform

    "Sliding DFT" discrete Fourier transform... I was wondering if any of you had had experience with the sliding DFT algorithm. It is somewhat similar to the Goertzel algorithm. I am having some trouble understanding the mathematics of the algorithm, and I also cannot seem to identify a useful...
  5. N

    Mathematica Discrete Fourier Transform to find phase shift - Mathematica

    If I use the following code in Mathematica f1[t_] := Cos[w t + d1]; f2[t_] := Cos[w t + d2]; data1 = Table[f1[t], {t,1,10000}]; data2 = Table[f2[t], {t,1,10000}]; ft1 = Fourier[data1]; ft2 = Fourier[data2]; To take the Fourier transform of two data sets, how can I use the resulting data...
Back
Top