PM_ME_VINTAGE_30S [he/him]

Anarchist, autistic, engineer, and Certified Professional Life-Regretter. I mosty comment bricks of text with footnotes, so don’t be alarmed if you get one.

You posted something really worrying, are you okay?

No, but I’m not at risk of self-harm. I’m just waiting on the good times now.

Alt account of [email protected]. Also if you’re reading this, it means that you can totally get around the limitations for display names and bio length by editing the JSON of your exported profile directly. Lol.

  • 3 Posts
  • 237 Comments
Joined 1 year ago
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Cake day: July 9th, 2023

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  • PM_ME_VINTAGE_30S [he/him]@lemmy.sdf.orgtoMemes@lemmy.mlMath
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    17 days ago

    Sounds like fun! I’m going to bed soonish but I’m willing to answer questions about multivariable calculus probably when I wake up.

    When I took multivariable calculus, the two books that really helped me “get the picture” were Multivariable Calculus with Linear Algebra and Series by Trench and Kolman, and Calculus of Vector Functions by Williamson, Crowell, and Trotter. Both are on LibGen and both are cheap because they’re old books. But their real strength lies in the fact that both books start with basic matrix algebra, and the interplay between calculus and linear algebra is stressed throughout, unlike a lot of the books I looked at (and frankly the class I took) which tried to hide the underlying linear algebra.








  • DSP (digital signal processing) is the field of applied mathematics and engineering dedicated to transforming and manipulating digital signals.

    Examples of real digital signals include audio files, image files, video files, and digitized recordings of various physical quantities by computers like the configuration of a robot as it moves in time, measurements of the processes in a factory, the trajectory of a spacecraft — almost anything that can be periodically sampled and take on a finite set of values [1] can be seen as a digital signal.

    DSP includes using tools like the Discrete Fourier Transform (DFT), the Z-transform, wavelet analysis, probability, statistics, and linear algebra to do things such as filter a signal (example: audio equalizer), predict future values (example: weather forecasting), data compression (example: JPEGs), system identification (example: fit a model of the earth to predict seismic activity), control (example: make a DC motor to respond to position commands), and stabilization (example: keep plane from “wanting” to smash into the ground). Particularly, it requires a careful consideration of the effect of sampling a signal (example: if done carelessly, you can make the sampled system unstable [read: explode]), as well as an interpolation process of some kind if you plan on using that signal outside your computer (example: you want to hear an audio signal stored on your computer).

    I got into DSP because I was an audio engineer and musician [2], and I wanted to design my own audio plugins. IMO I think almost everyone would benefit from some knowledge of DSP, but the math is really intense. Personally, I found out late in life that I have a nearly infinite appetite for math, so it’s a good fit for me.

    Here’s a playlist about DSP if you’re interested.

    [1] Actually, a lot of basic DSP books don’t restrict the signal to be in a finite set because it makes the math easier if the signal could be any real number. However, certain structures that would be exactly equivalent in theory are not equivalent on a real computer because ordinary computer arithmetic is approximate.

    [2] I still play music, but not as much as before engineering school.




  • PM_ME_VINTAGE_30S [he/him]@lemmy.sdf.orgtoMemes@lemmy.mlGuess I'll just burn
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    1 month ago

    If your signal looks like f(t) = K•u(t)e^at with u(t) = {1 if t≥0, 0 else}:

    • If Real(a) > 0, then your signal will eventually blow up.
    • If Real(a) < 0, then you signal will not blow up. In fact, your signal will have a maximum absolute value of |K|, and it will approach zero as time goes on.
    • If Real(a) = 0, it is either a complex sinusoid or a constant. In either case, it is bounded with maximum absolute value of |K|. It very much does not blow up.

    So e pops up all the time in stable systems and bounded signals because the function e^at solves the common differential equation dx/dt = ax(t) with x(0)=1 regardless of the value of a, particularly regardless of whether or not the real part of a causes the solution to blow up.





  • way more than $π million.

    I don’t need more than $π million. I just need enough to get some stuff started. I’m not interested in getting rich.

    I would also use the first loop to take medical tests of my health as much as possible since it wouldn’t matter if I went into debt in the first loop.

    Fair enough, but I really need the charm. I’m autistic and I’m not good at being social. I’d definitely be willing to give up a few years of life for more charm.