4/27/2023 0 Comments Fft scilab example![]() ![]() This means that we need to use “element-wise” multiplication, where the first element in CarrierSignal is multiplied by the first element in BasebandSignal, the second element in CarrierSignal is multiplied by the second element in BasebandSignal, and so forth. We are trying to replicate typical analog multiplication, where the instantaneous value of one signal is repeatedly multiplied by the corresponding instantaneous value of another signal. In this situation we don’t want to perform matrix multiplication (and actually it’s not even possible, because the number of columns in the first matrix does not equal the number of rows in the second matrix). In the Scilab environment, CarrierSignal and BasebandSignal are matrices, and if you use only an asterisk with two matrices, Scilab assumes that you want to perform matrix multiplication. One very important detail is the period in front of the asterisk. Here is the corresponding Scilab command: The carrier is represented by the sin(ω Ct) term, so what we’re doing here is shifting the baseband signal up (such that its values are always positive) and then multiplying the carrier by the shifted baseband. The basic mathematical relationship for amplitude modulation is as follows: Generating Frequency-Domain Plots for Modulated Signalsįirst, let’s set up our Scilab environment with variables that we will need throughout the rest of the article.īasebandSignal = sin(2*%pi*n / (SamplingFrequency/BasebandFrequency)) ĬarrierSignal = sin(2*%pi*n / (SamplingFrequency/CarrierFrequency)) Spectral analysis can also help us to really understand what’s happening when we perform modulation time-domain plots include details that are unnecessary when the goal is to ponder the fundamental interactions between the frequencies of the baseband signal and the frequency of the carrier signal. The short answer is as follows: The spectrum of a modulated signal gives us an intuitive, clear representation of important information that is difficult-or in some cases virtually impossible-to extract from a time-domain plot. Well, for a full answer to that question I recommend the first textbook page listed in the Supporting Information section. Why, then, do we need to generate a frequency-domain plot? Modulation creates changes that are evident in a time-domain plot of the modulated signal. This article should be more interesting: we’ll use discrete-time Fourier analysis to gain insight into the effects of amplitude modulation. However, the FFT analysis performed in the previous article wasn’t particularly useful-it merely informed us that the sinusoid had one spectral component at a frequency that we specifically selected at the beginning of the procedure. In a previous article, we introduced Scilab’s fft () command and discussed how we can manipulate FFT results so that they convey clear information about the amplitude of frequency components in a sampled signal. The Many Types of Radio Frequency Modulation (and other pages in Chapter 4 of the RF textbook).Learning to Live in the Frequency Domain (from Chapter 1 of AAC’s RF textbook).Scilab’s FFT functionality can help you understand the frequency-domain effects of RF modulation techniques.
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