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Hi, I want to learn DSP and find any of it's applications so i could finish a paper/project, how should i start and what applications should i look into?

Hi everyone,

I'm new to uncertainty quantification and I'm working on a project that involves predicting a continuous 1D signal over time (a sinusoid-like shape ) that is derived from heavily preprocessed image data as out model's input. This raw output is then then post-processed using traditional signal processing techniques to obtain the final signal, and we compare it with a ground truth using mean squared error (MSE) or other spectral metrics after converting to frequency domain.

My confusion comes from the fact that most UQ methods I've seen are designed for classification tasks or for standard regression where you predict a single value at a time. here the output is a continuous signal with temporal correlation, so I'm thinking :

• Should we treat each time step as an independent output and then aggregate the uncertainties (by taking the "mean") over the whole time series?
• Since our raw model output has additional signal processing to produce the final signal, should we apply uncertainty quantification methods to this post-processing phase as well? Or is it sufficient to focus on the raw model outputs?

I apologize if this question sounds all over the place I'm still trying to wrap my head all of this . Any reading recommendations, papers, or resources that tackle UQ for time-series regression (if that's the real term), especially when combined with signal post-processing would be greatly appreciated !

Need a reccomendation for some DSP books which has theory and problems to solve

I have heard of proakis and sk mitra can anyone help which to choose?

Hello,

This is my first time creating and deploying a filter on FPGA.

I am taking help of MATLAB Filter Designer App. Creating a 50 order IIR Chebyshev 2 Lowpass filter.

In MATLAB simulations the filter is working as expected but when we go to HDL I am unable to verify how it is working. I am not getting output or error.

So my question is How to proceed from having a HDL code and integrating it with any design

Hi all, I’m taking an Image Signal Processing class this semester and was wondering if anyone knows of any good 2D signal processing textbooks/references that has helped them a lot.

Thanks!!

I’m sampling data at 100Hz (every 10ms) using a 32bit processor.

I’m trying to reduce the delay of the filtered output. A delay of 0.5s (50 sample times) is unacceptable. A delay of 100ms (10 sample times) may be ok. I consider myself a newbie to signal processing.

Filters I’ve Tried:

• LPF - not happy with delay, not sharp enough cutoff
• Cascaded LPF  - 2 or 3 stage - delay gets pretty extreme, but happy with it reducing higher frequency signal 
• EMA Filter - similar results as basic LPF
• Moving Average - I forget why this one didn’t work for me - likely too large a delay to achieve decent low pass filtering
• Wavelet - computationally too heavy
• Notch filter - could not get that to work (tried a couple times - could be lack of coding skill)

Filters I’m Considering:

• Butterworth - concerned this may still have some delay
• Chebyshev 
• CIC
• Kalman Filter (new to me and will require quite the study - math refresher)

I'm making a rudder control for my dinghy, fun little project. I won’t be able to do any testing for 8 months…but could get a head start on the code so that I can test it when I get back to the boat. Any help is appreciated.

hi there
i want to start coding and build by own drum synth.
the drumsynth should include a pattern generator, modulation, granular processing, effects, sample players, recorder and buffered processing.

the idea is to eventually flash it on a teensy and build a working hardware box with midi in, out and 4x mono out.
i know how synthesizers and sequencers work but i do have close to no coding experience so a big community,
a modular workflow and libraries would be a big plus.
hybride environment would be ideal, a combination or the option to switch between code and nodes.

i have heard of faust, puredata, maxmsp, super collider but i know there are some more options.
which one would you recommend and why?

many thanks in advance!
beep beep

Hi guys, I am currently working on a project that uses real-time signal processing to detect sirens on the road for those who are hard of hearing. I was exploring a few methods, but I am not sure about how go about this, especially for real time processing. I was exploring time-frequency analysis, but the processing time seems very long. Are there any recommendations you guys could give me for this project? Ill pay like $10 via zelle for anyone who can give me a good direction to go

Usb-i s are darn expensive, this needs extra stept like programing?

and ideally able to differ between types of beats: kick/snare/hi-hat?

I was looking for interfaces Im a newbie noob. And i came across what is dsp about when i saw UA Volt and Apollo,their differences,my question is why would i need all those mixing/mastering buttons when the daw has already its own?

Hello Guys, Im trying to remove background/base oscillations from a signal by taking the FFT of the part of the signal that interests me(for example second 10 to second 20) and removing the base oscillations, that I assume are always present and don't interest me, by subtracting the FFTo of a part before what in interested in (e.g. 0-10 seconds). To me that approach makes sense but I'm not sure if it actually is viable. any opinions? Bonus question: in python, subtracting the arrays containing the FFT is problematic because of the different lengths, is there a better way than interpolation to make the subtraction possible? Thanks!

Hi there! i'm working on something and i have some difficulties on finding a solution to my problem. So i'm currently working on a biological signal (Post occlusive reactive hyperaemia). To simplifly it you register the bllod flow with Laser Doppler Fluxmetry for like 5 min then ou create an occlusion for 5 min then you realise the blood flow and register it for 5 min. i've got the data from an excel file and i'm supposed to identify a couple of parameters after identifying the begining and the end of the ocllusion from the signal. So the solution i tought of was using derivative since for both the end and the start of the occlusion we have a big change of slope (if i my say, i'm not an english native speaker) but both my detections happen right at the beginning of my signal. The occlusion part is the lowest one between 0.031 to 0.035 (second i guess, even though it's not actualy seconds) .So all my other parameters are not correctly detected. so if somone could give me some advice it would be great. I could have use wavelet but for the exercise it is forbiden. We have to do develop a new method from scratch.

https://preview.redd.it/lmfoxpcmedee1.png?width=1648&format=png&auto=webp&s=ac79b7cfa6691ed39870d23ee70815c94e6491d5

Also, i don't know if it's data related but in my excel file the data relative to the time are in a personalised format (mm:ss,0) but i find myself having a hard time converting them in seconds for my plots and calculation i obtain some weird number as you can see in the picture i attached.

Hi! I got the following question from my professor: 'assume you set up a transfer function model for data collected with a measurement interval of 1 minute (from the following form: y(k) = y(k-1)*0.9 + 0.4*u(k-1) e.g.), but now you want to use it in an application where you can only measure every 5 min. Do you need to change something? If yes, what would you change and how would you do it?' I was thinking that I should indeed change the parameters, and that I could use for example the time constant and steady-state gain calculated via the first model (TC = (measurement interval)/a-parameter; SSG = a/(1+b)) since these would be properties of the system, and than calculate the new parameters via the same formula. Is this plausible? Thanks! :-)

Hello I am an embedded systems engineer with a basic knowledge of DSP. As I am also playing guitar, bass and synth, and I ve been soldering analogue pedal clones. I want to dive into the digital realm now.

I am doing this as a learning opportunity as I am mostly a C developer and I want to learn better C++. Also my embedded platform is daisy seed board that I have successfully ran examples and set up my own project with bypass and some potentiometers. In the future maybe I will try a zynq chip as well.

Now before going to the embedded boards I would like to have the effects tried on my desktop computer , maybe make vsts out of it, and port in the embedded boards. If there are already developed DSP blocks I wouldn't mind. I did a small research about audio Dev in Linux and I see a lot of options. I lean more towards juce framework with cmake. I have a Scarlett focusrite interface on my computer and I play around with reaper daw.

So what would you recommend?

I'm trying to better develop intuition on how to interpret the results of a PSD versus amplitude scaled FFT. Currently, I think of them as one in the same since I can't think of any practical differences how I would view them. Can anyone provide practical applications where you would use one method of analysis versus the other?

I am thinking about plugins like Eventide SplitEQ or WavesFactory Quantum.
Has their been some new paper that came out and they both relied on or is it just new ideas with old tech?

I am currently a web developer doing JavaScript apps and have been working in tech for about 8 years. I am curious about the possibility of career-hopping into audio/DSP work. I figure such a transition will be a multi-year effort at least, so having a clear vision of what I'm aiming towards would help, hence this post looking for information from people in the field.

Why does audio software engineering and DSP interest me?

• Web apps feel like they are all the same and I don't find the challenges very gratifying to solve. I'm interested what else is out there.
• I love programming, I enjoy math, and I'm good at both. My favorite programming problems are ones that use math in an interesting way to solve problems, and I have convinced myself that DSP is math-heavy (true?).
• My number one hobby has always been music, and for the past many years I've exclusively worked with digital music either in DAWs or digital keyboards. Working adjacent to digital audio feels like it would be a great marriage of interest, ability, and economic viability.

Questions

Feel free to answer any or all!

1. Based on what I wrote above, does an audio/DSP-related job sound like a decent fit?
2. If you work with audio software or DSP, do you like your job? (I know this is totally anecdotal)
3. Any recommendations for resources? I'm currently working through Designing Audio Effect Plugins in C++ which includes some basic DSP theory. I know I'll need to go much deeper in order to potentially make a career hop.
4. Are there any job boards specific to audio engineer work that I should keep an eye on? Or even job titles that I could search on general-purpose job boards? My goal here is to keep a pulse on skills and requirements so I know I'm building towards the right things.

I have some code to detect the start of the SSB in some 5g recorded data. I want to start demodulating things, but I am only getting partial demodulation matches. I think it's because I'm not applying phase compensation coefficients to the subcarriers and therefore when I FFT the PSS for example, some of the subcarriers have some additional initial phase offset.

From what I understand in order to estimate some coefficients you need to measure the phase noise on a reference channel. But I'm mostly confused on where to find those reference channels. I feel like the easiest way to do it is in the frequency domain by FFT the reference channel and getting a coefficient for each of the 127 subcarriers in the PSS for example.

I'm busy doing the Jon Dattorro reverb in a vst plugin. I managed to get the first part working (I think).

https://whyp.it/tracks/246979/untitled?token=BGDxW
The second half is with input diffussion (the quieter part). I have no clue if what I did is right. The code I wrote for it looks like this:

Sample32 InputDiffuser::getSampleOut(Sample32 sampleIn) {
  feedforward = this->multiplier * sampleIn;
  delayedSample = this->buffer->exchangeSamples(sampleIn);
  sampleOut = delayedSample + feedforward + this->feedbackSample;
  this->feedbackSample = delayedSample * this->multiplier * -1.0f;
}

https://ccrma.stanford.edu/~dattorro/EffectDesignPart1.pdf figure 1 is the schematic. I have adjusted the amount of samples of the delays proportionally to the 44.1KHz my DAW is running in (see table 1). I have kept the multipliers the same as in table 1.

Looking at the waveforms in my DAW, it does look like the waveforms are a lot more smeared out and do not have any noticeable peaks compared to the ones without the input diffusing.

EDIT: There was a bug in my implementation. The code I had did not correctly implement the input for the delayline. The delay line in my above example was fed the inputsample with no processing whatsoever, but what needed to be fed into the delay line was the sum of the sampleIn - this->multiplier * this->feedbackSample. Anyone who is curious, it was supposed to be:

Sample32 InputDiffuser::getSampleOut(Sample32 sampleIn) {
  summedInput = sampleIn - this->multiplier * this->feedbackSample;
  feedforward = this->multiplier * summedInput;
  delayedSample = this->buffer->exchangeSamples(summedInput);
  sampleOut = delayedSample + feedforward + delayedSample;
  this->feedbackSample = delayedSample;
}

This sounds a whole lot more musical then the buggy example I initially posted. The buggy code also had nasty resonances at certain frequencies that made it 10dB louder at 880 Hz.

I was graduated in 2008 as an electronic engineer in UK. I was interested in DSP and my project was digital communications. After graduation, I went back to my home country and struggled to find a DSP job, and eventually went for DSP firmware jobs. There aren't much DSP related task in those jobs. I was thinking of going back to UK as there were much more DSP career there. Long story short, I have now settled in UK with ILR after working as embedded software engineer for 5 year. I find myself kind of stuck and unable to find a good DSP job opportunity to move on. DSP jobs in UK seems scarce as compare with 5 to 10 years ago. Do you think it's a good move to jump to DSP from embedded software. If so which direction to go? I'm into digital telecommunication or audio.

Hello, i want to generate a sine wave with frequency 1.2GHz. Is this possible that i will generate a signal in few MHz like 100MHz than DUC will increase its frequency. I am new to signal processing so dont have clear image of DUC what i know is it can up sample the input signal so my doubt is can it increase freq also? Also I am using ZCU111 RFSoC. if anyone have done such work before please help me. Also i have to use only PL part of the RFSoC.

Does anyone have any idea on how to replicate plate reverb dispersion in an algorithmic reverb? I've had success modeling the dispersion within a spring reverb where the high frequencies take longer to travel through cascaded allpass filters in a fb loop. However, this method does not work in the opposite way, that is to slow down the travel of low frequency. I can't find any resources on how folk go about doing this but I've seen it done in many a lot of vst such as Valhalla Plate.

This is the graph. I think I understood the demonstration to get both the general definition of PSD and the one for unipolar NRZ, but I still don't get how to read these graphs. Can someone enlight me?

I am interested in learning more about embedded DSP software. I have a modest background in audio DSP, and I have been reading Making Embedded Systems by Elecia White. I would be really interested in putting the two together, or at least reading about how that would work. Any recommendations or resources on the topic would be much appreciated!

Currently working on a bunch of audio projects for a low end mcu, one being speech coding, which further proved I need better workflow for testing/tuning the algorithms. Current one is the IDE for the microcontroller and an online c++ compiler for writing and testing the individual pieces and whole algorithm. Also visualizing the results on plotly online. Biggest problem is not being able to hear the results while developing, except for actually flashing my custom dsp board with each change and processing the audio with it, that's a huge hassle since I have to constantly reconnect audio and programming cables.

I usually start mocking up concepts in a DAW or pure data, but in some cases the only way to test a theory is directly writing it in C.

Basically I need a way to write and test dsp programs in C/C++ on windows or mac os with a simple audio interface api and console output for debugging. Also I really want to avoid Visual Studio.

Anybody have any thoughts on this course on statistical signal processing?.

Part of my job is developing adaptive beamforming algorithms, i know how to code the algorithms from papers/book, feed the data and interpret the result but most of the time i wonder how exactly this adaptive/estimation process even work, i can understand some of it but not all of it and it takes a lot of time going through papers and articles to comprehend it and even then, i am not even sure i understood it.

I realized i have a shaky foundation in this, which is why i plan on taking a course or a couple of lectures. I am looking for a course/book that goes through the fundamentals of adaptive, estimation and detection theory, any suggestion?

Hello guys!

I have a question about fast fourier transforms and energy spectral density. I have vibration recorders at distance 5, 10 and 15 m from a blast with explosives. The vibration recorders are placed directly at bedrock to measure vibration velocities. When i process the signal from velocity and time to energy spectral density and frequency, i can see that the energy increases for some frequencies at increasing distance? I would greatly appreciate som input on whether this can be correct? My initial though was that i had processed the signal wrong, as i was expecting the energy spectral density to decrease as the seismic waves traveled through the ground?

Thanks in advance for any replies and help!

I am an Electrical (Electronics and Communications to be exact) Engineer undergraduate and apart from my coding classes the ones that I enjoy the most are revolves mostly around signal processing. I am currently studying AI/ML by myself on the side as well with some CV projects.

Also I was really into DAW’s and making electronic music when I was a kid. So taking the major subfields of EE into account, I feel like DSP is the way to go for me. However I can also go for a SWE route and not really get into this rabbit hole even more, as some people in this subreddit said it’s hard work for less money than a SWE.

So I have a few questions.

Would you recommend pursuing DSP? Are you happy with it?

Does it cross boundaries with ML? Can I do AI/Data stuff with it?

How is the competition and pay like, is it stressful?