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On the benefits of noise

tuga

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Interesting research on the benefits of noise:


Stochastic resonance and the benefits of noise: from ice ages to crayfish and SQUIDs
K. Wiesenfeld, F. Moss - Nature 373 (1995)

Noise in dynamical systems is usually considered a nuisance. But in certain nonlinear systems, including electronic circuits and biological sensory apparatus, the presence of noise can in fact enhance the detection of weak signals. This phenomenon, called stochastic resonance, may find useful application in physical, technological and biomedical contexts.


Stochastic Resonance in Acoustic Emission
M. Friesel - Journal of Testing and Evaluation 2000
https://www.astm.org/jte12074j.html (€/£/$)

Stochastic resonance allows below-threshold signals to be detected because of the presence of favorable background noise. In this paper the author describes stochastic resonance and anti-resonance and presents some examples to illustrate how these affect the detection rates of acoustic emission signals or ultrasonic pulses in low signal-to-noise environments. The author introduces the signal fraction, a measure for quantifying the fraction of detected events that contain a signal that appears to have advantages over the signal-to-noise ratio for certain kinds of data, and a formalism for calculating the probability of signal detection when the noise is a time-dependent sinusoid.


Tuning in to Noise
A. Bulsara, L. Gammaitoni - Physics Today 1996

Two sweeping generalizations can be made about most natural systems: They are intrinsically nonlinear and they operate in noisy environments. Examples abound, ranging from weather systems to oscillating chemical reactions to the movements of an eel. The most complex example is arguably the human central nervous system, flooded as it is with the “noise” of modern life.


(source: https://www.stereophile.com/content/playback-designs-mps-5-sacdcd-player-measurements)
 

tvrgeek

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Just what those of us who listen to music on our stereo know , as opposed to those who believe an single composite number bigger is always better and you can't tell the difference anyway tells all.

There are also a lot of studies on how to identify correlated signals from below the noise floor. Can we do electronically what our brains can do?

Can we take these studies and find factors that we can measure ( add or subtract) to make our brain believe what we hear is real? Why does a near prefect amplifier not sound better than one with 100 times the non-linear distortion to some, but not to others?

I can confirm by observation of operators being able to hear a signal well below the noise floor. Has anyone studied the capability of one's wife hearing a comment you make across the room in a noisy party? I know I can hear detail below the sound of the blood rushing through my ears.
 

solderdude

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There are also a lot of studies on how to identify correlated signals from below the noise floor. Can we do electronically what our brains can do?

Electronically we can visualize further below noise floors than humans can. Steady state signals in any case.

Just mix noise with music and you'll find that all we hear is noise. The music will be drowned. Yet many folks claim we can hear below the noise floor.
With steady state or morse type we can and some sonar operators that know what to listen for can pick up certain changes in noise. That doesn't mean we can hear music related signals in noise.

I know I can hear detail below the sound of the blood rushing through my ears.

That is because of the noise spectrum of the blood flowing. The frequencies that are not masked you can hear. There is no mystery there.

Wife's from kitchens ... yes they are capable of remarkable things.
 

Jim Taylor

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Can we take these studies and find factors that we can measure ( add or subtract) to make our brain believe what we hear is real? Why does a near prefect amplifier not sound better than one with 100 times the non-linear distortion to some, but not to others?

"Making our brain believe" something can be a problem. We can do it with auditory information, with visual information, and to a certain extent, with tactile information. In each case, we are forcing our brain to believe in something that does not exist. After all, if it could be proven to exist, then we wouldn't need to force our brain at all, because it could apprehend the facts. So although the effect can be very pleasant, making our brain believe that something-or-other is real can lead to errors in both perception and judgement.

As for the question about amplifiers, you've used the term "better". "Better" is a non-quantified term that means nothing to other people ..... only to the person using the word. Even then, it may mean different things on different days or under different circumstances. Data, on the other hand, means the same thing today or tomorrow, and here, or there or some other place. Jim
 

pma

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Just mix noise with music and you'll find that all we hear is noise. The music will be drowned. Yet many folks claim we can hear below the noise floor.
With steady state or morse type we can and some sonar operators that know what to listen for can pick up certain changes in noise. That doesn't mean we can hear music related signals in noise.

Attached is a mix of sine and noise, sine level is below noise level (22kHz BW), anyone may check audibility :). I bet that everyone will hear the sine tone below the noise.
 

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  • belownoise.zip
    1.1 MB · Views: 29

RayDunzl

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Ok, so I look at the spectrum of the file posted above:

1645215779995.png


Maybe a definition of "below noise" would be of interest...
 

pma

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Ok, so I look at the spectrum of the file posted above:

View attachment 187502

Maybe a definition of "below noise" would be of interest...
I was expecting this reply. You show spectrum analysis where the “noise bottom” depends on analysis bin width. However, noise is calculated by integration over the whole bandwidth, here 22kHz. You show noise with something like 1Hz bandwidth or so, Fs divided by number of samples in FFT. Bin width bottom is not the noise.

You need to show Vrms (or total power) in your analysis. Then filter the 1kHz by notch and try again.

Noise power
noise.png


Sine power
sine.png
 
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