![]() We can generate DFT data for a waveform by including the corresponding array as an argument in an fft() command. My guess is that some people who have often heard the term “FFT” are not familiar with the term “DFT.” The FFT (fast Fourier transform) is simply a name used to refer to algorithms that can efficiently perform DFT calculations you can learn more about the FFT here. If we want to generate this same type of information in the context of sampled signals, we can use the discrete Fourier transform, abbreviated DFT. The original Fourier transform is a mathematical procedure that takes an expression that is a function of time and produces an expression that is a function of frequency. The Fourier transform provides a way of identifying the frequency content of a signal. A frequency-domain representation of a single-frequency sinusoid isn’t very interesting, though, and in the next article we’ll look at frequency-domain analysis in the context of RF modulation. The primary goal in this article is to understand and gain experience with Scilab’s fft() command, which allows us to display waveforms in the frequency domain. In a previous article, I introduced Scilab and the concept of digital sinusoid generation, and we used the plot() command to display time-domain waveforms. The Many Types of Radio Frequency Modulation.Learning to Live in the Frequency Domain.In this article we’ll work with sinusoidal signals in the frequency domain using Scilab’s fast Fourier transform (FFT) functionality.
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