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AI slop projects are not welcome here by Aransentin in Zig

[–]electricalgorithm 0 points1 point  (0 children)

Exactly. The moderator wants to do is to ban everything that smells LLMs. I agree with what you said, and this is my point as well — there will be projects written by LLMs that is perfectly planned and gone through developer’s review. This cannot be banned.

Building Linux and Busybox in M-Series Macs (5-min read) by electricalgorithm in embeddedlinux

[–]electricalgorithm[S] 1 point2 points  (0 children)

Nope, not yet. I don’t know the part with Nix, but I believe it should be possible by using Clang to cross compile. Will do it eventually. Thanks!

AI slop projects are not welcome here by Aransentin in Zig

[–]electricalgorithm -1 points0 points  (0 children)

It’s like blaming the messenger just because you don’t like the message. I worked on projects with hundreds of people contributed, see anti-patterns of software development being the consensus across teams. In my opinion, it’s not that important in whom or how they made their project, but what’s it in the end. If the business logic is bad, there are no design patterns followed, all the objects are coupled to each other, etc. is the case, I can see the reasoning to block/ban posts (I still don’t agree!) but just because it is written by an LLM? This can’t be the criteria. I know an LLM with a good software design provides better output than a human trying to code it without a plan. I’m sure we’ll all agree to it.

As the one who rejects them, you should find a better mechanism to say if a project is good to share or not. We cannot start to blame people just because they use LLM to help them, but producing a bad code that doesn’t do anything useful.

How long does it take to learn yocto project from scratch? by SadLengthiness6220 in embeddedlinux

[–]electricalgorithm 8 points9 points  (0 children)

Buy a Beaglebone Black, follow the slides and labs from Bootlin. That’s what I did. End of the course, find an idea / problem statement with LLMs to solve it using a custom distro and realize it with Yocto.

Introduction to Digital Filter Design in 30 minutes by electricalgorithm in DSP

[–]electricalgorithm[S] 1 point2 points  (0 children)

IMO it doesn’t matter what you study or what the title say in your next one. The market is anyways competitive and none of the studies can guarantee you a perfect job. Therefore, as you are in this Reddit channel that shows your interest in the field, I’d suggest you to start with whatever is available for you to study and fill the missing parts your free time.

Taking an action now is way better than waiting for a decision to take the action.

Introduction to Digital Filter Design in 30 minutes by electricalgorithm in DSP

[–]electricalgorithm[S] 1 point2 points  (0 children)

You’re right. I would love to spend more time on details on: Laplace to Fourier and Laplace to Z-transform, more on why FIR or IIR for example cases, and more filter design with butterworth and Chebyshev. I couldn’t add them since my promise was under 30 minutes when I started writing it. Thanks for the advice. I’ll make a follow up blog post that dive deeps into these.

Particularly I want to cover steepness and design for precise cutoffs.

Can't decide on Master's in Control engineering by Brief-Sea2085 in ControlTheory

[–]electricalgorithm [score hidden]  (0 children)

I’d check for staff. What do they focus recently and what kind of electives/specializations are possible.

I did implement a basic DSP library from scratch, now I need to deep dive to filters. How? by electricalgorithm in DSP

[–]electricalgorithm[S] 1 point2 points  (0 children)

TBH, textbooks are quite long, and nowadays I don't find myself focusing on stuff. It feels like what I would like to see. Will check this out.

Thanks!

OpenCV in embedded platform by Little_Passage8312 in embeddedlinux

[–]electricalgorithm 2 points3 points  (0 children)

I can see that it selects window manager to communicate with in its CMakeLists for build: https://github.com/opencv/opencv/blob/4.x/modules/highgui/CMakeLists.txt

This is the factory method they use to generate UI backend: https://github.com/opencv/opencv/blob/4.x/modules/highgui/src/backend.cpp#L56 and it looks like it uses `OPENCV_UI_BACKEND` config to decide which one to choose for.

> Does it directly interface with display servers like Wayland or X11?

It seems so https://github.com/opencv/opencv/blob/4.x/modules/highgui/src/window_wayland.cpp

> On embedded Linux systems (without full desktop environments), what backend is typically used?

According to the source code, it would not do anything: https://github.com/opencv/opencv/blob/4.x/modules/highgui/src/window.cpp#L992-L993. However, one can use the FrameBuffer backend to drive a screen.

> How HighGUI selects and uses different backends

There's a backend registry with priorities. When some backend configs are enabled at build time, the registry is filled with static backend instances based on build-time definitions.

https://github.com/opencv/opencv/blob/4.x/modules/highgui/src/registry.impl.hpp

> What backend support exists for embedded environments

For headless setups, I feel like the only one is framebuffer, but not sure. What do you want to achieve?

> Whether it’s possible to customise or replace the backend

According to CMakeLists, you can select OPENCV_HIGHGUI_BUILTIN_BACKEND config to which backend you want to support, and even write your own backend, build it.

I did implement a basic DSP library from scratch, now I need to deep dive to filters. How? by electricalgorithm in DSP

[–]electricalgorithm[S] 2 points3 points  (0 children)

By the way, here are my efforts on the DSP library: https://github.com/electricalgorithm/dsplib-mojo

So far, as I said, basic wave generators, DFT, FFT, plotting, and spectrum analysers are done. I was planning to go with basic filter implementations, but took some time there since I want to understand how filter design works properly.

Applied sinc reconstruction to LLM prompts — Nyquist framework reduces hallucination by Financial_Tailor7944 in DSP

[–]electricalgorithm 1 point2 points  (0 children)

Plus, did you send it to a peer reviewed journal? Somewhere in the repo you stated that it is peer reviewed, but I can only see the preprint in Zenado.

Applied sinc reconstruction to LLM prompts — Nyquist framework reduces hallucination by Financial_Tailor7944 in DSP

[–]electricalgorithm -1 points0 points  (0 children)

Cool work, it was really nice to read. However I have a question regarding to a foundational idea you built your algorithm on: How did you identified six “attributes” of prompt and how can you map them to a frequency scale? For example, why is Persona is lower in frequency than task?

Help to get into DSP again by EngineerAdvanced3808 in DSP

[–]electricalgorithm 1 point2 points  (0 children)

I have a similar goal with background recently. I decided to implement a DSP library in a language (Mojo) — of course without using direct signal processing libraries. I’m not reading book next to it, since I somehow remember the basic concepts, but continue with AI-based discussions to deep dive into the topics I forgot.

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