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24 Threads found on edaboard.com: Spectrum Estimation
First to start: Yes, you will damage the spectrum analyzer by applying 12 V DC to its RF input. Inside there is a precision RF attenuator with 50 Ohms nominal impedance. DC input will burn the first resistor and repairs are costly. To understand the spectrum analyzer use, please find Agilent White Paper on spectrum Analyzers. Operation (...)
Hi everyone, I'd like if someone can help me to understand how to perform the DC channel estimation in terms of noise, interference etc with some instruments (multimeter, spectrum analyzer..) of a car. I thought to make these measures using the cigarette lighter of a car to sense the entire circuit. In a few words I need to "see" how i
Hi everyone, I'd like if someone can help me to understand how to perform the DC channel estimation in terms of noise, interference etc with some instruments (multimeter, spectrum analyzer..) of a car. I thought to make these measures using the cigarette lighter of a car to sense the entire circuit. In a few words I need to "see" how i
Hi all. I have data matrix y(80x200). I'm trying to find AR spectrum estimation using Covariance method (pcov) for orders 10,50,100. But It gives an error at order 100. What should I do to fix it? (like zero-padding, maybe?) Or am I not able to use order 100? x=y; %y(80x200) order=100; nfft=80; pxx = pcov(x,order,nfft
Hi all. I'm doing some spectrum estimation. Here are codes, I used Welch method (without using pwelch func.) with no overlap. Now I want to do it with %50 overlap to see the difference, which parts should I change for this purpose? Fs = 8000; x = y1; %80x1 matrix Nx = length(x); w = hann(Nx); xw = x.*w; nfft = N
Hi all, There are various methods through which we estimate spectrum of a random signal like parametric and non parametric methods. But when I googled as for why we do spectrum estimation I don't get any answers. Can anybody tell me some instances which you would have come across for which u needed to estimate the (...)
I checked out a method for spectral estimation that estimates the spectrum of speech from degraded speech (speech+noise) input which involves autocorrelation. But i fail to understand how autocorrelation would achieve this. Wasn't autocorrelation meant for checking out the similarities between two points in the same signal right?
Hi there, I came across a question for which i am not sure of the answer. The question is as follows; Use a diagram to briefly explain how the signal's length affects its power spectrum estimation. Please provide me the answer Best regards David
Hi there, I want to know what are the factors influences the accuracy of estimating the power spectrum for a section of discrete signal and what techniques can be used to improve the accuracy of estimating a signal's power spectrum I would be much obliged if you can help me Thank you
spectrum estimation
Mean square error of the channel estimation, Capacity of the channel, the spectrum of the Tx and Rx signal.
I dont think studying sdr will make writing a code for spectrum sensing any easier ---------- Post added at 18:02 ---------- Previous post was at 18:01 ---------- sorry omarion but I don't agree with this. I would suggest you (object poster) to study spectrum estimation techniques of DSP[COLOR="Silver
Hi dear I need to calculate Average Normalized Power spectrum Density(ANPSDs). Is it possible by MATLAB. Please share your experience. I would be gratful.
hi! i need matlab coading for 'Power spectrum estimation using Periodogram' for matlab version 7.. if any one can help me out plzz do it asap
Regular conducted emission measurement is voltage across an equivalent circuit of grid impedance, so a current measurement isn't exactly the same. But it can give a rough estimation of emission spectrum and intensity. Generally, an oscilloscope current probe is a good tool. A selfmade current transformer (e.g. a torroid core with a suitable numb
In the same paper see the references 8,9,24,25,93,99 Look for spectrum analysis and time delay estimation techniques.... Hope that helps BRM
Hi, I have an image whose power spectrum is to be estimated. I read in a couple of books that there r 2 methods to go about. 1) parametric and 2) non-parametric. One of these methods (non-paramteric) was the indirect method of getting the autocorrelation function and then taking the fourier transform of the Autocorrelation function. Do you
Hi, You need to study some basic DFT theory and realtions between time frequency domain. DFT supposes periodic signals with infinite duration. Also you need some informations about windowing functions and spectrum estimation.
I need to create these two signals: 1. Non-stationary signal : for STFT analyzing and Wavelet analyzing. 2. Non-Gaussian signal: for Double-spectrum estimation. I've done some simulations using Matlab, but with no satisfied results. Maybe it's because of the source signals.. Could you please tell me how to create the above two signals prop
I am studying spectrum estimation and the book I have doesnt provide good examples. I would appreciate if someone direct me to material where I can find good and direct-simple examples, particurlary the periodogram method, Blackman-Turkey Method, and Parametric estimation -autoregressive model, yule walker equation. It is gonna be (...)