Signal processing is an electrical engineering subfield that focuses on analysing, modifying and synthesizing signals such as sound, images and biological measurements. Electronic signal processing was first revolutionized by the MOSFET and then single-chip digital signal processor (DSP). Digital signal processing is the processing of digitized discrete-time sampled signals. Processing is done by general-purpose computers or by digital circuits such as ASICs, field-programmable gate arrays or specialized digital signal processors (DSP chips).
Hackaday has published an in interesting series of articles on signal processing, and here are some picks from it:
RTFM: ADCs And DACs
https://hackaday.com/2019/10/16/rtfm-adcs-and-dacs/
DSP Spreadsheet: IQ Diagrams
https://hackaday.com/2019/11/15/dsp-spreadsheet-iq-diagrams/
Sensor Filters For Coders
https://hackaday.com/2019/09/06/sensor-filters-for-coders/
DSP Spreadsheet: FIR Filtering
https://hackaday.com/2019/10/03/dsp-spreadsheet-fir-filtering/
Fourier Explained: [3Blue1Brown] Style!
https://hackaday.com/2019/07/13/fourier-explained-3blue1brown-style/
DSP Spreadsheet: Frequency Mixing
https://hackaday.com/2019/11/01/dsp-spreadsheet-frequency-mixing/
Spice With A Sound Card
https://hackaday.com/2019/07/03/spice-with-a-sound-card/
- check also A real-time netlist based audio circuit plugin at https://github.com/thadeuluiz/RTspice
Reverse Engineering The Sound Blaster
https://hackaday.com/2019/06/19/reverse-engineering-the-sound-blaster/
FM Signal Detection The Pulse-Counting Way
https://hackaday.com/2019/08/28/fm-signal-detection-the-pulse-counting-way/
DSP Spreadsheet: IQ Diagrams< https://hackaday.com/2019/11/15/dsp-spreadsheet-iq-diagrams/
Here is an extra, not from Hackaday, but an interesting on-line signal processing tool for generating sounds
https://z.musictools.live/#95
223 Comments
Tomi Engdahl says:
95% of those who pretend they can tell the difference between a wav file and an MP3 are lying to themselves. I’m talking about 320kbps MP3s, not 128 or below.
A blind test would fool most people (it’s been done). The differences are so subtle that, unless you really listen specifically to hear the differences, you wouldn’t be able to tell lossy from lossless. And who does that? Most people listen to music on the go, or while doing something else, or in less than favorable environments.
And it’s even more true with the mainstream devices that most people possess. Very few people actually own high-end amplifiers and speakers. Most people are not trained to listen to music critically, and just don’t care that much about the sound quality (to a certain extent).
Therefore, MP3 is perfectly acceptable in most cases, but if you prefer lossless formats because you are convinced you can tell the difference, that’s all fine.
For casual listening, it absolutely does not matter if it’s MP3 or lossless.
Oh, yes, and also, not all recordings and mixing are good in the first place.
Tomi Engdahl says:
Grebz Bibert and FM sound processors like early Omnia’s in the 90-ties didn’t like mp3 at all, especially lower bitrates like 128 or 160 kbps.
Tomi Engdahl says:
Grebz Bibert True. But there is also a noticeable step from 16/44.1 and 24/96. It’s not so much the actual specs but the breathing room of more bits which allows imperfect levels to still shine through when turned up.
Tomi Engdahl says:
LAME improved algorithms by adding so many configuration options that didn’t exist in Fraunhofer. The two most powerful ones are: joint-stereo that encodes (L+R) & (L-R) instead of L & R, and Variable Bit-Rate (VBR), though not all players can play or seek it properly xD
Tomi Engdahl says:
Fun fact: the very first mp3 song was Tom’s Diner(Susanne Vega)
Tomi Engdahl says:
Light Transport And Constructing Images From A Projector’s Point Of View
https://hackaday.com/2025/08/07/light-transport-and-constructing-images-from-a-projectors-point-of-view/
Imagine you have a projector pointing at a scene, which you’re photographing with a camera aimed from a different point. Using the techniques of modelling light transport, [okooptics] has shown us how you can capture an image from the projector’s point of view, instead of the camera—and even synthetically light the scene however you might like.
The concept involves capturing data regarding how light is transported from the projector to the scene. This could be achieved by lighting one pixel of the projector at a time while capturing an image with the camera. However, even for a low-resolution projector, of say 256×256 pixels, this would require capturing 65536 individual images, and take a very long time. Instead, [okooptics] explains how the same task can be achieved by using binary coded images with the projector, which allow the same data to be captured using just seventeen exposures.
Construct an image from a projector’s point of view (and more tricks with light transport)
https://www.youtube.com/watch?v=TcXMf0mTh94
Tomi Engdahl says:
White Balance is Broken
https://www.youtube.com/watch?v=WADuXiMZxq4
00:00 – What is White Balance?
00:49 – How is White Balance Broken?
02:03 – Why is White Balance Broken?
02:54 – Comparison with Exposure
04:55 – How to Fix White Balance
05:52 – Takeaways
06:49 – Ps…
Tomi Engdahl says:
Audio DiffMaker
Some Example DYF Files
These “dyf” files can be downloaded and played within Audio DiffMaker. Each “dyf” contains a set of related audio WAV files that you can play side-by-side and simultaneously to compare by ear, and then to listen to just the extracted Difference signal.
https://www.libinst.com/diffmaker_example_files.htm
Audio DiffMaker
signal difference extraction software
from Liberty Instruments
https://www.libinst.com/Audio%20DiffMaker.htm
Audio DiffMaker is a freeware tool set intended to help determine the absolute difference between two audio recordings, while neglecting differences due to level difference, time synchronization, or simple linear frequency responses.
The difference recording that results is only what has changed between the two recordings. If anything – a change of component, a treatment, mechanical damping, etc. – is having any audible effect on the audio signal in a system, the difference recording will have audible content. The end result is primarily intended to be evaluated by ear.
This relatively simple idea can be used demonstratet whether some products can alter audio signals in audio equipment.
Changes detected by Audio DiffMaker are not necessarily audible changes for any given person. Some changes will not sound different, and some are too weak to be heard when accompanied by the unchanged part of the program material. But a silent difference track can only result if the two tracks being compared are unchanged (the same).
The DiffMaker process, by its very nature, avoids masking effects because it removes the large signal that masks subtle details. Unlike traditional listening tests, differences can be detected even when buried by program material or if affected by imperfect components in the system.
What Can Audio DiffMaker Do?
Some of the tools within Audio DiffMaker can be used to:
Precisely align two similar audio tracks to the same gain levels and timing
Extract and listen to even very tiny differences between pairs of audio tracks
Quickly compare two or more recorded audio signals under precisely gain-matched and time-matched conditions.
Measure the frequency response of the equipment being tested and apply it so the effects of linear frequency response can be removed from the testing.
Record sounds at various sample rates and bit resolutions up to 24bit/192kHz with the “Recorder” tool.
Select and copy sections of audio tracks, trim them, or “rip” them from audio CDs, with the “Trimmer/Ripper” tool.
Quickly see the responses of devices or entire audio systems (even rooms) using the included high resolution 1/6th octave frequency/spectrum “Response Analyzer” and matched pink noise source.
Compact multiple WAV files, and a text description, into one easily transported “DYF” file. Just double-click on a DYF file in Explorer and Audio DiffMaker will open and load the files, ready for listening.
When to use Audio DiffMaker?
Testing for audible effects of
Changing interconnect cables (compensation for cable capacitance may be required)
Different types of basic components (resistors, capacitors, inductors)
Special power cords
Changing loudspeaker cables (cable inductance may need to be matched or compensated)
Treatments to audio CDs (pens, demagnetizers, lathes, dampers, coatings…)
Vibration control devices
EMI control devices
Paints and lacquers used on cables, etc.
Premium audio connectors
Devices said to modify electrons or their travel, such as certain treated “clocks”
Different kinds of operational amplifiers, transistors, or vacuum tubes
Different kinds of CD players
Changing between power amplifiers
General audio “tweaks” said to affect audio signals (rather than to affect the listener directly)
Anything else where the ability to change an audio signal is questioned
Doesn’t this process require ultra-high end recording equipment?
No, because DiffMaker doesn’t try or need to accurately reproduce music — it is only trying to help detect whether anything has changed, which is a much less demanding requirement. It doesn’t matter if the difference that DiffMaker finds might not be perfectly reproduced — only that the difference is left intact enough to hear.
The sound card used doesn’t need to be completely transparent or of highest pedigree. It only needs to be capable of responding to any differences that may occur (even if those differences aren’t reproduced perfectly) and of not burying any significant differences in added noise.
How can you tell whether the equipment was good enough in a DiffMaker result? You can listen to the result, and note the level of any difference and/or decide if any remaining noise is high enough to be maybe covering something that may be important. In other words, if the gear isn’t good enough, you’ll be able to hear it, it won’t make a difference go silent.
Tomi Engdahl says:
How to test amplifier distortion with REW
https://www.youtube.com/watch?v=H9-60-tGvI0
Tomi Engdahl says:
https://www.diyaudio.com/community/threads/does-making-distortion-measurement-of-cable-make-sense.373384/page-5
Tomi Engdahl says:
To measure hi-fi cable distortion, use a spectrum analyzer to observe the output spectrum, identifying harmonics and their relationship to the fundamental frequency. Alternatively, a distortion analyzer can be used to measure the difference between the input and output signals after removing the fundamental frequency.
Methods for Measuring Hi-Fi Cable Distortion:
1. Spectrum Analyzer:
A spectrum analyzer displays the frequency spectrum of a signal, showing the magnitude and phase of each frequency component.
By injecting a sine wave into the cable and analyzing the output, you can identify harmonics (multiples of the fundamental frequency) and their amplitudes.
Harmonic distortion is then calculated by comparing the amplitude of the harmonics to the fundamental frequency.
2. Distortion Analyzer:
A distortion analyzer, also known as a THD (Total Harmonic Distortion) analyzer, measures the distortion introduced by a device (like a cable).
It works by injecting a low-distortion sine wave into the cable and then filtering out the original sine wave frequency.
The remaining signal represents the distortion products (harmonics and noise).
The analyzer then calculates the THD by comparing the level of the distortion products to the level of the original sine wave.
3. Audio Analyzer Software:
Software like Room EQ Wizard (REW) can be used with an audio interface (e.g., Focusrite Scarlett) to measure distortion.
These tools can generate sine waves and analyze the output, providing measurements of THD and other distortion metrics.
Example using a Distortion Analyzer:
1. Setup:
Connect the distortion analyzer to the input and output of the cable.
2. Injection:
Generate a low-distortion sine wave (e.g., 1 kHz) and inject it into the cable.
3. Filtering:
The analyzer’s notch filter removes the original sine wave frequency from the output.
4. Measurement:
The remaining signal (distortion products) is measured, and the THD is calculated and displayed.
Key Considerations:
Sine Wave Purity:
A pure sine wave is essential for accurate distortion measurements.
Clipping:
Avoid exceeding the cable’s or amplifier’s clipping point during testing, according to a forum post.
Context:
Distortion measurements are specific to the equipment used (cable, amplifier, etc.) and the test conditions.
Subjective vs. Objective:
While objective measurements are important, subjective listening tests can also be valuable in assessing the audible impact of distortion.
Tomi Engdahl says:
https://forums.audioholics.com/forums/threads/using-a-distortion-meter-or-oscilloscope-to-see-distortion.116215/
https://www.nutsvolts.com/magazine/article/build-a-basic-audio-distortion-analyzer
https://sound-au.com/articles/distortion.htm
Tomi Engdahl says:
In Hi-Fi systems, cable distortion and signal source quality both contribute to the overall audio fidelity, but they affect the sound in different ways. Cable distortion, such as capacitive effects or signal interference, can introduce subtle changes to the signal’s waveform, while the signal source itself (e.g., a turntable, CD player, or DAC) can introduce its own inherent distortion and noise.
Cable Distortion:
Types:
Cable distortion can manifest as various forms of signal alteration, including:
Capacitive effects: Long cables, especially those with high impedance sources, can act as capacitors, attenuating high frequencies and potentially causing a loss of clarity.
Interference: External electrical noise can be picked up by cables, especially if they are not properly shielded, leading to hum, hiss, or other unwanted sounds.
Non-linear distortion: Cables can introduce subtle non-linearities in the signal, causing harmonic or intermodulation distortion.
Impact:
Cable distortion can reduce the overall clarity, detail, and dynamic range of the audio signal.
Minimizing:
Proper cable selection (e.g., using shielded cables), careful cable management (keeping them away from power cords), and using shorter cables can help minimize cable-related distortion.
Signal Source Distortion:
Types:
Signal source distortion can arise from various factors, including:
Non-linearities in components: Amplifiers, DACs, and other components can introduce non-linearities, especially at higher volumes or when pushed to their limits.
Noise from components: Noise can be generated by various components within the source device, such as power supplies or digital circuitry.
Mechanical or electrical issues: Issues with turntables (e.g., rumble, motor noise) or other sources can also contribute to distortion.
Impact:
Signal source distortion can significantly impact the overall sound quality, potentially masking details, introducing harshness, or reducing the sense of spaciousness.
Minimizing:
Investing in high-quality source components, ensuring proper grounding and power conditioning, and minimizing vibration can help reduce source-related distortion.
In essence: Cable distortion can be thought of as introducing subtle alterations to the signal, while signal source distortion can be more pervasive, affecting the overall character and fidelity of the sound. It’s important to address both to achieve optimal audio quality
Tomi Engdahl says:
https://www.reddit.com/r/audioengineering/comments/m08q4a/what_is_the_difference_between_distortion_and/
Tomi Engdahl says:
Unbalanced cables introduce NOISE but they do not necessarily add distortion. Distortion is usually caused by clipping.
Tomi Engdahl says:
https://www.audiocheck.net/
Tomi Engdahl says:
https://www.audiocheck.net/audiotests_stereo.php
Tomi Engdahl says:
https://en.wikipedia.org/wiki/Head-related_transfer_function
Tomi Engdahl says:
The (Data) Plot Thickens
https://hackaday.com/2025/08/28/the-data-plot-thickens/
You’ve generated a ton of data. How do you analyze it and present it? Sure, you can use a spreadsheet. Or break out some programming tools. Or try LabPlot. Sure, it is sort of like a spreadsheet. But it does more. It has object management features, worksheets like a Juypter notebook, and a software development kit, in case it doesn’t do what you want out of the box.
The program is made to deal with very large data sets. There are tons of output options, including the usual line plots, histograms, and more exotic things like Q-Q plots. You can have hierarchies of spreadsheets (for example, a child spreadsheet can compute statistics about a parent spreadsheet). There are tons of regression analysis tools, likelihood estimation, and numerical integration and differentiation built in.
Fourier transforms and filters? Of course.
If you’ve been putting off Jupyter notebooks, this might be your excuse to skip them. If you think spreadsheets are just fine for processing signals and other big sets, you aren’t wrong. But it sure is hard.
LabPlot
FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone and trusted by professionals
https://labplot.org/
Your First Data Import and Visualization in LabPlot
https://www.youtube.com/watch?v=Ngf1g3S5C0A
LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone. Download LabPlot now at https://labplot.kde.org/download/. In this short video you’ll learn how to import your data into LabPlot and visualize it quickly.
Drops Of Jupyter Notebooks: How To Keep Notes In The Information Age
https://hackaday.com/2019/02/22/drops-of-jupyter-notebooks-how-to-keep-notes-in-the-information-age/
DSP Spreadsheet: The Goertzel Algorithm Is Fourier’s Simpler Cousin
https://hackaday.com/2020/11/13/dsp-spreadsheet-the-goertzel-algorithm-is-fouriers-simpler-cousin/
Tomi Engdahl says:
Visualize your data using ggplot. R programming is the best platform for creating plots and graphs.
https://www.youtube.com/watch?v=rfR9Nrpfnyg
Your First Data Import and Visualization in LabPlot
https://www.youtube.com/watch?v=Ngf1g3S5C0A
Tomi Engdahl says:
How To Plot Functions in LabPlot
https://www.youtube.com/watch?v=dMmQmExjbU8