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 PM_ME_VINTAGE_30S@lemmy.sdf.org. 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.

  • 2 Posts
  • 112 Comments
Joined 1 year ago
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Cake day: July 9th, 2023

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  • Amazon Fire Tablet 7in. I bought it literally just to read PDFs, and it was so slow that it was basically unusable. I tried switching out the launcher to something more minimal (Niagara launcher I think), and I figured out how to disable the ads that were all over the place. It helped a bit, but not enough to overcome the hardware and Fire OS. (I think I needed ADB for both of those fixes; I had to put in some real work to unfuck that tablet.) Plus the screen was too small for my pathetic human eyeballs.

    Was it worth $30? At the time, yeah, because I literally couldn’t afford anything else, but I now have an $80 10in generic Android tablet that’s wildly faster.








  • 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.




  • Infinite-dimensional vector spaces also show up in another context: functional analysis.

    From an engineering perspective, functional analysis is the main mathematical framework behind (1) and (2) in my previous comment. Although they didn’t teach functional analysis for real in any of my coursework, I kinda picked up that it was going to be an important topic for what I want to do when I kept seeing textbooks for it cited in PDE and “signals and systems” books. I’ve been learning it on my own since I finished Calc III like four years ago.

    Such an incredibly interesting and deep topic IMO.


  • I actually designed a digital equalizer using an IIR filter this semester, which actually does theoretically work on sequences of numbers, which constitutes an infinite dimensional vector space. The actual math was just algebra and programming, but it was an implementation of a Z-transform transfer function which is a sequence operator (maps input sequence to output sequence).

    IMO infinite-dimensional stuff shows up in two types of problems:

    1. For some reason, you need to solve the partial differential equation you started with, i.e. you can’t use symmetry or approximations to simplify it into an ordinary differential equation.

    2. When you’re dealing with signals that change in time or space, you have to decompose those signals into simpler signals that are easier to analyze.



  • IMO LyX is way simpler than LaTeX for basic stuff, but because it is literally not Microsoft Word I couldn’t really use it to collaborate with people this semester, let alone convince them to work on a full LaTeX document. LyX would be the way to go if my colleagues were even remotely interested in learning about literally anything. You can lead a horse to water, but you can’t make it drink…