Signal Processing with Paul

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@seal9821 13 күн бұрын

Great video!

@kvelez 17 күн бұрын

\documentclass{article} \usepackage{blindtext} % dummy text \usepackage{graphicx} % \usepackage{apacite} % APA citation style \title{\textbf{\LaTeX{}} Citation} \author{Author} \date{May 15th, 2024} \begin{document} \maketitle \blindtext[3] \pagenumbering{roman} % roman page numbers ewpage \tableofcontents ewpage \section{Introduction} % numbering must be visible for Contents Table \blindtext[1] \cite{rashid2019cloud}. \subsection{Image Insertion} % the * hides the numbering \begin{figure}[h] \centering \includegraphics[scale=0.7]{xsquared.png} \caption{The symbol $x^2$} \label{fig:xsquared} % label for reference \end{figure} \vspace*{1cm} Insert figures like Figure ef{fig:xsquared}. \begin{verbatim} \begin{figure}[h] \centering \includegraphics[scale=0.5]{xsquared.png} \caption{The symbol $x^2$} \label{fig:xsquared} % label for reference \end{figure} \end{verbatim} ewpage \section{Tables} \begin{table}[h] \centering \begin{tabular}{|c|c|c|} \hline Name & Age & Address \\ \hline John & 25 & 123 Main St. \\ \hline Jane & 30 & 456 Park Ave. \\ \hline Mary & 35 & 789 Elm St. \\ \hline \end{tabular} \caption{People's Information} \label{tab:people} \end{table} ewpage %\bibliographystyle{apacite} % APA bibliography style \bibliographystyle{plain} \bibliography{mybib} % bibliography file \end{document}

@Elaiassais 29 күн бұрын

Thank you for the video, unfortunately it seems to be a premium feauture

@kyu5378 Ай бұрын

3:34 결국에는 돈내야하네 시간낭비하게 만드냐...

@sirlimonada2 Ай бұрын

Paul, I found your channel recently and it has been quite useful, do you have any idea if you can denoise data from a signal stored as an array using a noise profile? I took some measures with an osciloscope in the lab and it had a consistent background noise, and I thought that maybe I could store some of the noise and then use it to clean a bit my data, like you can do with audio editing I'm guessing you can use fft but maybe there's a package that can do this easier instead of having to build it myself Thanks beforehand

@neeleshgupta3491 Ай бұрын

Thank you dude!

@adityanagarkar4326 Ай бұрын

Here you have sampled the signal at intervals of 1. what if I want to sample it at a higher frequency?

@code2compass Ай бұрын

What is your question?

@bransap 2 ай бұрын

Super helpful! Appreciate you making this series.

@pelasgeuspelasgeus4634 2 ай бұрын

It's easy because it's wrong. Any equation containing the imaginary unit i=sqrt(-1) is a complete HOAX.

@idreeskhan-zp5ey 2 ай бұрын

Thnak You!

@eyita_admas 2 ай бұрын

thank you for your lovely lesson but when try to integrate zotero to latex it says it is premium about could give if there is free please

@SignalProcessingWithPaul 2 ай бұрын

I think you do need a premium account unfortunately. If you are in school ask your department if you can get access; my PhD advisor pays for it for all of us, and many schools will too.

@angelchavez4824 2 ай бұрын

Do you have any sources for saying Euler discovered the Fourier series first

@ProfeARios 2 ай бұрын

Thank you so much for sharing. Best regards from Panama 🇵🇦

@robbyhidayahramadhan9663 2 ай бұрын

thanks bro

@brianweik8001 3 ай бұрын

Thanks for such an excellent video. I was a mathematics undergrad and wanted to do a Fourier refresher. Looking forward to the series (Pun intended!)

@skilz8098 3 ай бұрын

You know what's even better than this? Writing the actual source code for an FFT and its inverse then watching them work. Excellent video by they way, very enjoyable.

@SignalProcessingWithPaul 3 ай бұрын

There's no better way to understand it than having to write the code yourself :)

@skilz8098 3 ай бұрын

@@SignalProcessingWithPaul True, but the actual source code is easier to read and understand compared to the actual mathematical integral notation. Now as for the comparison of them from a Graphical representation such as transposing them from one spectrum to another is fairly easy. Their overall concepts are quite simple... the algorithms aren't too bad, but the math involved to derive them is quite complex, pun intended.

@skilz8098 3 ай бұрын

@@SignalProcessingWithPaul Well other than FFTs, one of the most other beautiful things in math is e^(i*x) = cos(x) + i*sin(x) as well as e^(i*pi) = -1 or e^(i*pi) + 1 = 0. These have to probably be two of my favorites... Then again Quaternions are up there, and so is Boolean Algebra.

@user-wn7rf1tc8g 5 ай бұрын

Hi Paul, first let me say - thank you. your explanations are clear , clean and very good, liked it very much. I would like to ask you, if you could read a small WAV file or even an existing CSV file with 2 columbs (t, xt)- of a sinus signal, read it in to python, and then do the exact thing that you did here in this video ? (plot the original signal, then sample is in NYQUIST freq., plot it and then plot the two- one over the other to see the comparition between the two?

@angeloc700 5 ай бұрын

Nice video. As a suggestion, if you turned the VS autocomplete dialogues off, I’m sure the viewer’s experience would be much better; it’s very difficult to focus on what you’re saying and typing when modal boxes are popping up and changing all over the place.

@SignalProcessingWithPaul 3 ай бұрын

This is good suggestion, thanks

@robertmoran 5 ай бұрын

I talked about this when teaching at Pratt back in the day. Magenta and yellow equals Red. Cyan And yellow equal Green and magenta and yellow equals red. Love the scientific answer to why this so. Excellent to a fault. :)

@anonymousguy438 6 ай бұрын

How to know what are the different frequencies which constructs your main signal? I am asking about the frequency values not its amplitude.

@SignalProcessingWithPaul 3 ай бұрын

I may make a video on this. To answer your question, it will be divisions of the sampling frequency of your signal (which is 1/T, where T is the time interval between samples). Given a sampling frequency Fs and N samples in the time domain, each index of the FFT will be at k*Fs/N. However at Fs/2, (meaning for all indices larger than N/2), the frequency "wraps around" and becomes negative due to aliasing. So I believe the frequency can be written concisely as (k*Fs/N) - ((N - k)*Fs / N * I(k > N/2)), where I is the indicator function.

@thiagodavidmoreiramadeiros4458 6 ай бұрын

Really nice video, it helped me alot! Thanks

@acelaox6836 6 ай бұрын

Thank you so much now I didn't know about fftshift in numpy till today!

@imk820 7 ай бұрын

Hi can I ask you a question?

@SignalProcessingWithPaul 6 ай бұрын

Yeah sure, go for it

@thiagodavidmoreiramadeiros4458 6 ай бұрын

@@SignalProcessingWithPaul Hi, I am working with a sinusoidal signal made of two different frequencies that i have to find. How can i get the indexes that correspond to these frequencies when i apply the fft

@mpreceptor2049 8 ай бұрын

Laplace transform integral from ZERO to infinity.

@SignalProcessingWithPaul 8 ай бұрын

There’s a unilateral (0+ to infinity) and a bilateral laplace transform (-infinity to infinity) - which one you choose depends on your initial conditions. If you’re working with causal signals they’re the same. Whoever taught you Laplace transforms should have clarified that both are valid, because it is wrong to say the “correct” Laplace transform is the unilateral one.

@dmitridiaguilev3990 8 ай бұрын

The guys is full of interesting insight into how to look at complex analysis problems

@dmitridiaguilev3990 8 ай бұрын

Good overview of Fourier and an intro to complex circuit analysis. Staying for next video to watch the elaboration of the technique.

@SignalProcessingWithPaul 8 ай бұрын

Thanks so much :), lots more planned. Let me know if there are any topics you want me to cover

@_ifly 6 ай бұрын

great explanation. Would you be able to provide some programming tutorials on Ti mm-wave signal processing?@@SignalProcessingWithPaul

@markcalvelo1909 8 ай бұрын

This is great thank you

@SignalProcessingWithPaul 8 ай бұрын

Glad you found it helpful :)

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