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Power Spectral Density and Total Power Calculation for Signal

By the Wiener–Khinchin theorem, the power spectral density (of a power signal) is equal to the Fourier transform of the autocorrelation function. Therefore, one way to proceed is to analytically ...
Steve J.'s user avatar
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Frequency content of a noisy signal

Couple of mistakes! #1 Take the fourier transform of its power signal (square the noisy signal) That's for anything but a constant zero signal not the same as the PSD estimate you get from your #2. ...
Marcus Müller's user avatar
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Finding mean, autocorrelation, and power spectrum of $y[n]=(x∗h)[n]$ where $x[n]$ is zero mean white gaussian noise

Assuming $h(t)$ is the impulse response of a linear system, there are many ways to get to the desired result. Here's one for the Power Spectrum: By definition, the power spectrum $S_{y}(\omega)$ of a ...
Jdip's user avatar
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