Everywhere in the exact sciences there's the dualism between statistical analysis and
deterministic engineering tools, since the major break through in quantum physics at the
beginning of the 20th century. Whether that's some sort of diabolical duality or, as it
actually is at the higher levels of mathematics, some natural state of affairs with on one
side theoretical science that properly decorrelates what's not connected and the better
beta scientists construct working theories and machinery on the basis of deterministic
("analytic" or number based) hypotheses depends in my opinion on the nature of the beast.
In physics, the strong and hard mathematical foundation of the main solutions for the
quantum mechanical equations of name comes primarily from physical observations: nature
appears to play a lot of dice at some level, whether we like it or not! That's a real
given, not a lack of high frequency measurements or lack of practical knowledge about
electromagnetics, waveguides and linear and non-linear electronic networks, but as of a
century ago until this day, because of physics laws that in incredible accuracy appear to
be based on pure statistics, and hard givens about "causality".
Electronics in the higher frequency ranges, since the beginning, are usually designed in
terms of networks (oscillators, mixers, amplifiers, cables), EM field considerations
(antennas, waveguides) and a quantum mechanics at the level of transistor design. There
are many fields around communications obviously in progress the last decades, including
better measurement equipment and better high speed digital processing tools, as well as
design software for creating (digital) transmitters and receivers.
Recently I've witnessed Agilent software for mobile phones and other applications digital
transmitters and other circuitry, and had some hands on experience with Keysight
technology oscilloscopes in the many tens of giga Hertz range. Pretty interesting to
actually being able to sample signals of 10s of GHz into a computer memory and for
instance do eye-based analysis on digital signals, or play with the various statistics
modules in such a device.
I heard the story that some of the latest Xilinx high speed FPGAs with their 28Gb
transceiver links when connected over a back-plane create working "eye" diagrams, i;e; the
communication works good, but measurement equipment fails to acknowledge this by proper
measurement. That's an interesting EE design dilemma right there: is the measurement
equipment better than the design at hand, or: do you need a bigger and faster computer
than the target computer system you're designing, etc.
So the statistics being discussed come mainly I think from electronics about information
theory, and some people, as is normal in inf. th. find it fun to take out some singular
(simpler) components like basic statistical signal considerations, in the hope to easily
design some competing digital communication protocols. Scientific relevance: close to
zero, unless maybe you'd get lucky.
With respect to musical signal analysis, it could be fun to theorize a bit about corner
cases that exist since a long time, like a noise source feeding a sample and hold circuit,
and making interesting tones and processing with that. Like a S&H unit from a classical
60's modular Moog synthesizer, which probably can be clocked with varying clock, and
feedback signals. The prime objective at the time was probably more related to finding out
the deep effects of sampling on signals, and encoding small signal corrections in analog
signal for when they where going to be on CD. My guess...
T.V.
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