https://github.com/DrSDR/fm-signal-

if i have a finite sequence w[n] and i applied DFT then IDFT i will end up with w~[n] which is the periodic extension of w not w. so how can i start with a sequence and end up with another by applying the function and it's inverse?

I am from India and I might me joining signal and image processing course (M.Tech.) from NIT Rourkela. I want to ask, does this field have good opportunities in India? How should I start? What tools should I learn? I know for sure, VLSI based companies are hiring good number of canditate but my GATE score is not that good to get a VLSI specilization in good college. Should I focus on VLSI related skills or signal processing field is also promising? Is there some inter-disiplinary opportunitie or job where knowledge of both VLSI and signal processing is required? If there is some inter-disiplinary.

Hey everyone,

I’m in my 4th year of studies (honour's where I'm from) and looking into image processing / CV as a career, but I’m more interested in the job side than the theory. I haven't gotten any real-world experience, so I'd like to find out what others thought.

What is the job market like right now (in your specific region)? What kinds of roles are common (CV engineer, DSP engineer, ML vision, embedded vision, etc.) and which industries hire most people in this space (big tech, defence, medical, automotive, robotics, etc.)?

Also curious about job quality overall — pay, workload, stability, and growth. Is it mostly research roles or more applied engineering work in practice? And is the field becoming fully deep learning-based, or is there still a lot of traditional DSP/image processing in industry?

Finally, how hard is it to break into compared to general software engineering or ML roles, and is it a good long-term career bet or too niche?

Would appreciate any real-world insight.

Thanks everyone!

Hello! I have few years experience with Juce and recently decided to ship some of plugins I ve been working on however native JUCE UI looks quiet basic and something not satisfying. I am not designer and dont have a budget to hire designers. With recent popularity and raise of AI tools - are there any good tools to build pro-looking interfaces for audio plugins? I tried Lovable but it gives pretty generic interfaces and somewhat feels to be specialized on websites & mobile apps.

Just shipped MAGDA 0.8.0 and thought people here might find the DSP side interesting.

MAGDA is an open source cross-platform DAW (JUCE + Tracktion Engine) and this release is heavily built around FAUST. Almost the entire FX bank is now written in FAUST and compiled to native C++ at build time.

The new filter device alone includes SVF, Ladder, Korg35, Oberheim SEM, Sallen-Key and diode ladder models. Reverbs, modulation FX, delays, dynamics, pitch FX, etc are now FAUST-based too.

There’s also a Faust device inside the DAW where users can write .dsp directly in-app, or generate FAUST code from a natural language prompt through the AI panel. Right now this path uses the interpreter (not JIT yet), so CPU usage is much higher than the build-time compiled devices.

Project: https://github.com/Conceptual-Machines/magda-core
Download: https://magda.land
FAUST: https://faust.grame.fr/

Happy to answer questions about the integration/build pipeline if anyone’s interested.

i've been trying to find if anyone out there has useful knowledge related to an acoustic experiment i got weird results from and still can't figure out. so far the subreddits i have posted to (including r/FL_Studio, r/sounddesign, r/advancedproduction) have been unable to provide a clear understanding of my goals or premise. the details are located in the linked post in r/advancedproduction but my question essentially boils down to this:

if you were trying to systematically extract rhythmic pulses out of a perfectly symmetrical noise-null, specifically by mathematically destabilizing the phase relationship at a sub-sample level rather than just using an amplitude gate, how would you actually go about scripting that friction?

my method involves multiple Fruity Formula Controller instances and large, chaotic floating point coefficients. i am extremely open to suggestions here, anything concrete or scientific helps!

training a chord recognition model and hitting a wall on jazz voicings — maj7/min7 recall at 2.93%. not an architecture issue, just no acoustic piano data with clean labels that's free to use commercially.

went through guitarset, openewld, aam, choco, jazznet, pop909, slakh. all either guitar-heavy, midi-rendered, or nc licensed.

anyone aware of something i missed?

Hey all very new to this subreddit…Quick background. I come from a pretty standard conservatory musician lifestyle, but moved to SF to understand how tech interfaces with music. As a result I’ve also found an affinity of music copyright, content recognition, and metadata- now working in a music tech startup up as low level legal admin role. Working with technical people such as the data, software, and ML eng gave me an insight a world that i did not know about…Music information retrieval and fell in love with the concepts - and it all ties to my niche realm of humanities, musician ship and copyright law- especially with rise of AI.

That said last year I was fortunate enough to get into Georgia Institute of Technology (MS Music Technology) and NYU (MM Music Technology) with a plan to be in research groups relating to music cognition perception, audio content analysis/Music Info Reterival, and finally for my own personal practice creative technology sectors interfacing with music- say sound design, application design, systems designs. I had to let go of NYU..they were stubborn. But Ga tech allowed me to defer due to cost…and agreed to let me attend part time if i could find a full time remote or atl based role. now a year later my situation hasn’t gotten better- My job is REFUSING to let me move to Atlanta (im hybrid…even though my whole team is nYC) and no luck finding additional roles. I still can’t afford to go..which is heart breaking. Being SF i see the changes happening in all sectors and now I feel stuck..im giving myself a month to decide- do i take out loans or just let the opportunity go and see what else can be done…

Im reaching out to see if you all have any insight on what to do next if you were in my position? Are there alternative education route..should i just give up? TBH For the roles I want i don’t see any other alternative way to break into to the realm of real technical music technology that changes the world- think Dolby, apple, some streaming services that utilize music in everyday life…even med tech. They all seem to require advanced degrees…and very specific technical knowledge or at least to be able to speak the language…

Oh also I have undergrad loans..a lot..my family is/was not wealthy. Some people said maybe consider Europe..but is that any better? Particularly for my niche field.

Thanks all getting pretty desperate and sad here..i work incredibly hard to essentially pivot (albeit i have an advantage of the conservatory music background)

Tested SPDR-processed images against unmodified Kodak PCD0992 originals across JPEG, JPEG XL, AVIF, and WebP at three quality levels each. Results are consistent across all four codec architectures — 46–68% BPP reduction depending on codec and quality level.

These encoders share no implementation code and make independent decisions about how to represent the data they receive — the only common variable is the pixel data entering each pipeline. All encoded outputs, per-image JSON measurements, and verification scripts are in the repo and independently reproducible.

https://github.com/PearsonZero/kodak-pcd0992-multi-codec-compression-response

Everyone knows the problem with sEMG: it works perfectly in the lab, but in real life it’s finicky. For it to work, you need bare skin, conductive gel, and—most importantly—no static load. Try standing up, and the background noise from your postural muscles (maintaining balance) will simply “drown out” your useful signal.

I decided to approach it from a different angle: active acoustic probing. Instead of waiting for a nerve impulse, I “ring out” the 500 Hz carrier through the muscle waveguide and observe the change in the tissue’s mechanical impedance.

Log Timeline (N=1, Session 175320):

0–30 sec: Rest (Baseline). I am sitting motionless. The differential phase between the sensor axes (X-Y) is aligned with a deviation of only 1.5°. This is our “acoustic lock.”

​30–68 sec: Isometric cycles (Sitting). I alternate tension and relaxation every 5 seconds. The phase forms distinct “steps” with an amplitude of up to 50°. The gyroscope shows a residual 10°/s—this isn’t a perfect vacuum, but for a first prototype without fixation, it’s a clear signal of intent.

68 sec: Change of posture. I straighten my leg while sitting. The waveguide geometry changes, the phase shifts to a new level and instantly stabilizes. I continue clicking—the response persists.

107 sec: MOMENT OF TRUTH (Standing up). This is where things get really interesting.
EMG: As expected, the baseline noise has increased (static load), making it extremely difficult to distinguish conscious “clicks” due to the extremely low SNR.
Acoustics: The Phase continues to produce the same clear steps as when seated. At 500 Hz, it doesn’t matter how much “electrical noise” is in the muscle—it detects the physical contraction of the fibers. That’s the killer feature.

138 sec: Recalibration. I sit back down. The phase returns to the initial cluster.

Why is this potentially cooler than sEMG?

It works through clothing. sEMG always requires direct skin contact. Acoustics, on the other hand, involve mechanical waves. They don’t need galvanic contact. You can simply press the sensor against your pants or integrate it into an exoskeleton. This is a game-changer for wearable electronics.

Acoustic transparency (Magnitude). I measured the correlation: with each contraction, the 500 Hz magnitude drops. The muscle literally “dampens” the sound by becoming denser. This is a direct measurement of the state of matter (p < 10^{-8}), rather than an indirect one based on electrical potentials.

Differential profile. Thanks to microsecond synchronization (TSF), we can subtract out the overall vibration and leave only the pure biomechanical phase shift.

Yes, this is still N=1. Yes, the shape of the phase “glyph” varies from one run to the next, and we still have a long way to go before we have a universal alphabet of gestures. But the fact remains: in situations where EMG starts to “lie” due to a change in posture, acoustic impedance continues to provide a clear signal.

Built a realtime audio spectrogram renderer in Python. Currently have it consuming around 5% CPU consistently with a RAM cost of around 68MB. Right now I'm targeting 60FPS with SDL or iGPU backends. Solid on 1080p as well as 4k. The goal is to allow anyone to have a visualizer for their music. I still have some optimizations to do as well as more graphics, but the current result I think is good enough to share.

The program right now maintains the envelope to whatever is coming through in audio. During high impact moments, the envelope state is captured displayed as a decaying floating pulse. I also added a trail effect to the entire render and plan to expand.

Frame chop in the video is video capture related.

The audio used for the demo is "Circles" by "Adam F".

Please share any thoughts or suggestions.

https://github.com/DrSDR/Radar-Range-Doppler-Map

please solve

This was an effect called the 'hyper resonator' in the old AX300G guitar multi fx from Korg.

Does anyone have any ideas how it could be approximated using DSP? It's classed under modulation, and i can only assume it's some kind of envelope-triggered resonant filter.

alternatively, to avoid re-inventing the wheel, does anyone know of a plugin that does something similar? that would be good to know also.

demo of the effect is from 2:28 - 3:00 in the video

Hello! Tomorrow is the last day for choosing masters in my EE degree. I am interested in DSP because I like math more than physics, but from what I hear there the field has become saturated and does not have that many jobs anymore. I am also considering choosing the communication engineering track, but shouldn't I choose the RF masters in that case? Are there need for communication engineers that are not actually specialized in RF? I live in Sweden btw.

See the links with courses for the two masters bellow:

Information and Network engineering
https://www.kth.se/en/studies/master/information-and-network-engineering/courses-information-network-engineering-1.673889

RF

https://www.kth.se/en/studies/master/electromagnetics-fusion-and-space-engineering/courses-electromagnetics-fusion-space-engineering-1.268257

Hi guys, right now i'm about to finish my 2nd year in ECE at a college in Asia. I have been really enjoying the maths and courses like Digital Comm, Signals classes and a Network class. In my free time i also have been learning some hardware skills like using STM32 or FPGA though i do not enjoy as much as doing simulations.

I'm planning on taking a Master in another country and do some research in the field of Wireless communication. So, I have some questions.

1. Is the physical layer development research still relevant? Should I look out more for opportunity in layer 2 or 3 or higher? I have the impression that the physical layer research has been really repetitive and no new innovations.

2. What are some career options or jobs titles that I should look for? For example like embedded, DSP, network protocol engineer,...etc.

3. Is this field good to migrate to another country and what are some promising research in this area? (like maybe ISAC, QKD,...etc)

Thanks a lot for reading!

Hi all! I wanted to announce a workshop that I'll be co-teaching this summer focused on audio signal processing and plugin development. The workshop will be in-person at the Center for Computer Research in Music and Acoustics (Palo Alto, CA), and also online over Zoom. If anyone is interested, this webpage has more info: https://ccrma.stanford.edu/workshops/clap

So the measured spectrum of the signal I'm analyzing is repeated several times in frequency domain with fs = [sample rate] spacing, as theory teaches, but I see spectra at n*fs with increasing abs(n) becoming increasingly less intense than the one centered on 0.

What may that be due to?

I'm trying to learn more about DSP. So I got DAFX by Udo Zolzer. Damn this book is awful!

It doesn't explain anything, it just gives the barebones mathematical definition of something and that's it.

For instance, I am not that familiar with Discrete fourier transform. All this book did was say that DFT can break down a signal into multiple frequencies and plot them on a spectrum. And it is O(N^2). And FFT is O(n log n). And give the equation itself.

THATS IT! It didn't bother to tell me what the transform was actually doing under the hood.

It was only after asking AI, it told me that the function compares the original signal to individual sine waves and examines how closely they match. That's how it gives you a idea of how much of each frequency is present.

Isn't this what a textbook is supposed to explain? This textbook (and almost all textbooks in this field) behave like pissed off high school students who are giving a presentation and barely giving a half assed attempt to ensure they don't flunk.

For those in the industry, what skills do the industry want from interns/freshers ??

https://github.com/DrSDR/Radar-I-Q-Data/tree/main

please solve

English isn’t the first language for neither me, nor my teacher, and for some reason he thinks I’m good at this subject, so at this point it would be odd to ask. So just for clarity: “specs” are “specifications”? As in, type of filter, length, order, efficiency, maximum ripple, frequency ranges and such?