Примери за използване на Discrete fourier transform на Английски и техните преводи на Български
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A simple example of the discrete Fourier transform.
Using the discrete Fourier transform is quite computationally intensive.
Approximation with the discrete Fourier transform.
The discrete Fourier transform and finite impulse response filters.
Using the inverse discrete Fourier transform.
The discrete Fourier transform of the function x(k) is defined with the formula.
The component H(n) of the discrete Fourier transform at n= f would be.
The discrete Fourier transform will be non-zero- approximately- at components 20 and 80.
On large sets of data,the FFT would be much faster than the discrete Fourier transform.
We can compute the discrete Fourier transform as follows.
First, the formula above uses only the real part of the inverse discrete Fourier transform.
Example- the discrete Fourier transform of a simple wave.
For a typical window, Hmax occurs at ω= 0 andis the 0th component of the discrete Fourier transform.
We chose to compute the discrete Fourier transform with N uniform points over 2 seconds.
Note that we could easily add the imaginary part of the inverse discrete Fourier transform above.
The magnitude of the discrete Fourier transform at these components is 100/ 2= 50.
The FFT is not a transform, butis rather an algorithm for faster discrete Fourier transform computations.
The following is the discrete Fourier transform of 500 points of the rectangular window.
The FFT, however,would also require log2(N) operations to perform the discrete Fourier transform split into smaller transforms. .
Example- discrete Fourier transform of a real valued complex signal.
We do not use the inverse discrete Fourier transform to produce a FIR filter.
Discrete Fourier Transform(DFT) is one of the fundamental operations in digital signal processing.
The magnitude of the resulting discrete Fourier transform components will be as in the following figure.
The discrete Fourier transform then poses one interesting question, namely what the component at 0 represents.
We begin with the inverse discrete Fourier transform of the desired ideal magnitude response.
The discrete Fourier transform of the function x(k) is defined with the formula.
The following graph compares the discrete Fourier transform of the Blackman window and the rectangular window.
With the discrete Fourier transform we can also compute the phase response of our low pass filter prototype.
The following graph shows the discrete Fourier transform of the flat top window against the transform of the rectangular window.
Take the discrete Fourier transform of a signal x(k) in discrete time k and apply Euler's formula.