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A typical approach would be the Pan-tompkins algorithm. You can also apply a first order low pass filter or a mean filter to improve results.


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Please see N.J. Kasdin, "Discrete Simulation of Colored Noise and Stochastic Processes and $1/f^\alpha$ Power Law Noise Generation", Proceedings of the IEEE, 83(5), (1995), 802-827. On page 806, Kasdin discusses the factor of 2 issue and states that "It is this author's belief that the factor of two in (24) is an error due to a broad-band bias introduced by ...


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Given the goal stated in the second sentence of your Preamble, this is what is possible using the Corsini and Saletti algorithm: More details, and the literature reference, at https://dsp.stackexchange.com/a/56820/41790. Hope this helps!


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With original image $o$ fixed, the higher, the better. If PSRN($o,d$) is bigger than PSRN($o,n$), you can claim an improvement in the decibel measure. It is difficult to interpret PSRN($d,n$), sinceyou compare two more-or-less noisy data. Is PSRN a good measure of subjective image quality remains an open question.


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I like the answer by @Laurent Duval and will give it an upvote. I also like the comments, especially that of @robert bristow-johnson, but I thought I would try doing what I suggested in the comments, which is basically (I think) what robert bristow-johnson essentially suggested. First, I made up a fluorescence spectrum that more or less matched what the OP ...


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Second try! This question is also at the Electrical Engineering stack, so I posted a short 'starter' answer there. A mod converted it to a comment and my tiny rep there prevented me making any further comments. This is what I posted there: I suggest this link to cbeleites's answer to a question involving laser-excited Raman spectroscopy: https://stats....


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I think that the question by OP xvan has several misconceptions in it and these propagate into the answer that he has provided for his own question. Define \begin{align}\phi_1(t) &= \sqrt{\frac 2T}\cos(2\pi f_ct),~ 0 \leq t \leq T,\\ \phi_2(t) &= -\sqrt{\frac 2T}\sin(2\pi f_ct),~ 0 \leq t \leq T, \end{align} where $f_c$ is the carrier frequency are ...


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Marcus and Ben have very clearly identified the problem: the signal is simply too small relative to the least significant bits (LSBs) of the "virtual machine"'s ADC. The sensible solution is to increase the signal by use of gain. From the provided plots, a signal gain around 100 would be a good starting value. Alternatively, the ADC resolution would have to ...


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Marcus is correct, so this means something else is wrong. The left equality simply shows that, for continuous time, the unilateral PSD, $S_x(f)$, is two times the Fourier transform of the autocorrelation function, $R_x(\tau)$. See, e.g., A.B. Carlson, Introduction to Communication Systems, 2nd Ed., McGraw-Hill, NY ©1975, Chapter 2, equation 18a. Or see ...


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So, you've got the audio signal in digital on your PC. Analyze that digitally; you don't need any measurement equipment to do that. On the contrary: Measuring properties of the analog audio signal is highly undesirable, because you'd be including the sound card of your laptop in your measurement, but you probably don't care about that even remotely. If you ...


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