IM Distortion, Speakers and the Death of Science


One topic that often comes up is perception vs. measurements.

"If you can't measure it with common, existing measurements it isn't real."

This idea is and always will be flawed. Mind you, maybe what you perceive is not worth $1, but this is not how science works. I'm reminded of how many doctors and scientists fought against modernizing polio interventions, and how only recently did the treatment for stomach ulcers change radically due to the curiosity of a pair of forensic scientists.

Perception precedes measurement.  In between perception and measurement is (always) transference to visual data.  Lets take an example.

You are working on phone technology shortly after Bell invents the telephone. You hear one type of transducer sounds better than another.  Why is that?  Well, you have to figure out some way to see it (literally), via a scope, a charting pen, something that tells you in an objective way why they are different, that allows you to set a standard or goal and move towards it.

This person probably did not set out to measure all possible things. Maybe the first thing they decide to measure is distortion, or perhaps frequency response. After visualizing the raw data the scientist then has to decide what the units are, and how to express differences. Lets say it is distortion. In theory, there could have been a lot of different ways to measure distortion.  Such as Vrms - Vrms (expected) /Hz. Depending on the engineer's need at the time, that might have been a perfectly valid way to measure the output.

But here's the issue. This may work for this engineer solving this time, and we may even add it to the cannon of common measurements, but we are by no means done.

So, when exactly are we done?? At 1? 2? 5?  30?  The answer is we are not.  There are several common measurements for speakers for instance which I believe should be done more by reviewers:

- Compression
- Intermodulation ( IM ) Distortion
- Distortion

and yet, we do not. IM distortion is kind of interesting because I had heard about it before from M&K's literature, but it reappeared for me in the blog of Roger Russel ( http://www.roger-russell.com ) formerly from McIntosh. I can't find the blog post, but apparently they used IM distortion measurements to compare the audibility of woofer changes quite successfully.

Here's a great example of a new measurement being used and attributed to a sonic characteristic. Imagine the before and after.  Before using IM, maybe only distortion would have been used. They were of course measuring impedance and frequency response, and simple harmonic distortion, but Roger and his partner could hear something different not expressed in these measurements, so, they invent the use of it here. That invention is, in my mind, actual audio science.

The opposite of science would have been to say "frequency, impedance, and distortion" are the 3 characteristics which are audible, forever. Nelson pass working with the distortion profile, comparing the audible results and saying "this is an important feature" is also science. He's throwing out the normal distortion ratings and creating a whole new set of target behavior based on his experiments.  Given the market acceptance of his very expensive products I'd say he's been damn good at this.

What is my point to all of this?  Measurements in the consumer literature have become complacent. We've become far too willing to accept the limits of measurements from the 1980's and fail to develop new standard ways of testing. As a result of this we have devolved into camps who say that 1980's measures are all we need, those who eschew measurements and very little being done to show us new ways of looking at complex behaviors. Some areas where I believe measurements should be improved:

  • The effects of vibration on ss equipment
  • Capacitor technology
  • Interaction of linear amps with cables and speaker impedance.

We have become far too happy with this stale condition, and, for the consumers, science is dead.
erik_squires
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If you continue to use such a narrow definition of computer OR artificial intelligence, you will never understand it. If I called it artificial life instead of artificial intelligence, would it be easier for you to understand?
Actually I think you got backward.  You can call it by whatever name, it's still computer AI based on algorithm.  


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I dont know why you treated him so arrogantly...

Guess who is right about the algorithm basis of A. I. ?
andy2 or heaudio123

I would suggest some education in AI if you want to participate usefully in discussions with AI. One can only lead a horse to water.
«Neural networks are a set of algorithms, modeled loosely after the human brain, that are designed to recognize patterns.»
https://pathmind.com/wiki/neural-network

Observe the presence of word ALGORITHM in this citation from wiki

Calling it artificial life will not transform it in a non-algorithmic miracle....


You accuse us in the beginning of not understand the Algorithmic set of equations behind neural networks but the way you define what is an algorithm here is false being too narrow:

That andy2 and mahgister and you kevin repeatedly describe it purely as algorithmic, i.e. the same data will always result in the exactly same answer to n-decimal places, clearly communicates that your knowledge of AI is rudimentary at best and hence you type long posts on an audio forum site
Your definition of algorithmic is too narrow here and does not correspond at all with the neural networks algorithm...You put it in our mouth perhaps with the back tought that it will be easy to refute that false definition of algorithm …But I dont think so.... I think you dont know the very general scope of the concept of algorithm linked to the Turing Concept...

Then not knowing what a neural network algorithm is you negate that A.I. neural network was in essence algorithmic...

You are assuming that AI is algorithmic and must follow the rules of a Turing machine. There is no such restriction.
But neural networks are algorithmic program …. Then?


Do you suppose machine will think with non algorithmical sauce?

I dont think that ….


I can develop my idea about Von Neuman Evolution and self replicating machine, also about the critics some mathematicians makes about Penrose use of Godel arguments, but I dont think you will be able to understand … 

One can only lead a horse to water.... :)