(no subject)
Jun. 9th, 2026 06:27 am![[personal profile]](https://www.dreamwidth.org/img/silk/identity/user.png){kind=small}
transitional_writesWhat about the application of the Solomonoff induction
to the RF sensing of human brain?
https://en.wikipedia.org/wiki/Talk:Solomonoff%27s_theory_of_inductive_inference
1. If we assume that the algorithmic complexity
of neural processes is relatively small
(you could take a look at the Potapov monography
for some arguments)
2. As far as I know a lot of neural processes in human brain are electric (or electro-chemistry)
in nature. They have a little power and a small
frequency (~ 1-1000 Hz).
So they emit very low frequency radio waves.
3. You can detect those radio waves on
small antennas if the impedance of such antennas
is matched. This is basically the citation
from the book on electrodynamics.
I uploaded one such book on Twirpix site.
4. So you can create a lot of such receivers
- microstrip filter to filter very high frequencies
- impedance matched microstrip antenna
- resistor for noise for oversampling
- very fast comparator to sample signal
in a very large array on a chip using
standard CMOS or some sort of full-custom process
(maybe even with some new materials)
5. BreamForming and large arrays of digital correlators with sub-mm positioning accuracy
could be achived.
so it seems there is no theoretical
obstacles to implement some sort of
RF human brain sensing or even control
if you can implement reverse structure
with array of a large amount of RF amplifiers
with sub-mm beam forming accuracy
BTW I wrote that remark:
https://en.wikipedia.org/wiki/Talk:Solomonoff%27s_theory_of_inductive_inference
What about the application of the Solomonoff induction to the person to person information exchange?
to the RF sensing of human brain?
https://en.wikipedia.org/wiki/Talk:Solomonoff%27s_theory_of_inductive_inference
1. If we assume that the algorithmic complexity
of neural processes is relatively small
(you could take a look at the Potapov monography
for some arguments)
2. As far as I know a lot of neural processes in human brain are electric (or electro-chemistry)
in nature. They have a little power and a small
frequency (~ 1-1000 Hz).
So they emit very low frequency radio waves.
3. You can detect those radio waves on
small antennas if the impedance of such antennas
is matched. This is basically the citation
from the book on electrodynamics.
I uploaded one such book on Twirpix site.
4. So you can create a lot of such receivers
- microstrip filter to filter very high frequencies
- impedance matched microstrip antenna
- resistor for noise for oversampling
- very fast comparator to sample signal
in a very large array on a chip using
standard CMOS or some sort of full-custom process
(maybe even with some new materials)
5. BreamForming and large arrays of digital correlators with sub-mm positioning accuracy
could be achived.
so it seems there is no theoretical
obstacles to implement some sort of
RF human brain sensing or even control
if you can implement reverse structure
with array of a large amount of RF amplifiers
with sub-mm beam forming accuracy
BTW I wrote that remark:
https://en.wikipedia.org/wiki/Talk:Solomonoff%27s_theory_of_inductive_inference
What about the application of the Solomonoff induction to the person to person information exchange?
no subject
Date: 2026-06-11 06:01 am (UTC)0515z ::ffff:80.234.76.107: Contact GPS experts and machine learning people.
0516z ::ffff:80.234.76.107: The most closest RF point are GPS experts with beamforming and large antenna arrays experties.
0520z ::ffff:80.234.76.107: beamforming is a technic to use several antennas to receive or transmit signals in a very precise direction. it is used in the LTE base stations and Starling
0520z ::ffff:80.234.76.107: you can reproduce it with KiwiSDR or HackRF
0520z ::ffff:80.234.76.107: there were some merged pull request to HackRF on this topic
0521z ::ffff:80.234.76.107: also the timestamp Verilog code that intersect GPS signal path and HF signal path in KiwiSDR is related to the beamforming techniq
0526z ::ffff:80.234.76.107: even if you think it is a joke or is in doubt about some points - send it as is to other radio and machine learning engineers pls
0526z ::ffff:80.234.76.107: but if you are in doubt - just ask some questions about point that is confusing you
0536z ::ffff:80.234.76.107: don't be stupid ppl
0536z ::ffff:80.234.76.107: think step by step
0536z ::ffff:80.234.76.107: ask questions if you are in doubt
0537z ::ffff:80.234.76.107: pls send it to other professional or amateur radio engineers AND machine learning people like https://github.com/opencv/opencv
0538z ::ffff:80.234.76.107: https://web.archive.org/web/20260611051113/https://transitional-writes.dreamwidth.org/44972.html
0541z ::ffff:80.234.76.107: send to KiwiSDR forums. is is open source, has GPS part, has low frequency part and have some simple form of signal merging as an example. Folks could understand and think step by step all that information
0542z ::ffff:80.234.76.107: I hope the only point that you could not believe is a relatively ease task to parse those RF dumps with something like https://github.com/opencv/opencv
0542z ::ffff:80.234.76.107: but make dumps and contact machine learning people
0547z ::ffff:80.234.76.107: or at least share it to everything! maybe at least one other reasearcher except for the Black Hat RF engineers from the Puting seret service willl try to reproduce it
0550z ::ffff:80.234.76.107: stop thinking about this "you could not believe is a relatively ease task to parse those RF dumps with something like https://github.com/opencv/opencv" as impossible task
0551z ::ffff:80.234.76.107: all other stuff should be familiar to the ordinary RF engineers and machine learning ppl. just try it
no subject
Date: 2026-06-11 06:28 am (UTC)https://web.archive.org/web/20260611035039/https://transitional-writes.dreamwidth.org/44972.html
1. Just take a simple worm.
2. It has a very simple neural net, that emits and recieve very low frequency radio waves.
3. Highly likely it may be useful to use short impulses, like in the PSU.
4. To send and receive even very low frequency waves you can use very short antennas if impedance is matched.
5. The modern beam forming is possible with the sub-mm accuracy, and with high speed sampling rate you can sample neurons group by group.
The next step depends on what is the real algorithmic complexity of the human brain and behavior is.
But to estimate it you can just take a look at the IPCAMERAS, and get that it is very small.
And the real algorithmic complexity of human brain is relatively low.
It seems the minimum description length principle could be used to deduce minimum ethics. At least you can compare ethics by the length. What about the following question: how to shoot met-art girl in the dark underground? ~2026-24709-41 (talk) 16:43, 8 June 2026 (UTC)
https://en.wikipedia.org/wiki/Talk:Solomonoff%27s_theory_of_inductive_inference
you can ask machine learning people about the next step of how hard is to recognize human brain processes from the radio wave dumps.
the answer may surprise you ppl
ask OpenCV or other signal processing ppl with the lean to the most general algorithms like https://en.wikipedia.org/wiki/Talk:Solomonoff%27s_theory_of_inductive_inference
the answer is surprising you, contact GPS experts ppl
Contact GPS experts and machine learning people.
The most closest RF point are GPS experts with beamforming and large antenna arrays experties.
beamforming is a technic to use several antennas to receive or transmit signals in a very precise direction. it is used in the LTE base stations and Starlink
you can reproduce it with KiwiSDR or HackRF
there were some merged pull request to HackRF on this topic
also the timestamp Verilog code that intersect GPS signal path and HF signal path in KiwiSDR is related to the beamforming techniq
even if you think it is a joke or is in doubt about some points - send it as is to other radio and machine learning engineers pls
but if you are in doubt - just ask some questions about point that is confusing you
and most important thing - of course I will not send it to oters
I will not post it to other forums just because I can
send it to others, at least as a joke. and try to reproduce at least for fun if you can
even if we don't tell about full control, we can just sample data, parse some simple signals and send it back
and it will give us partial control without solving the full task
at list we can really reduce complexity by that way
try it, share it
it, try it
think how to reduce the complexity and solve partial tasks if you still in doubt the general task is impossible to solve
share it, try it
think how to reduce the complexity and solve partial tasks if you still in doubt the general task is impossible to solve
even if you think the general task is impossible to achieve, something simple could be achieved. and it could surprise you
contact RF engineers and machine learning people
like that or other you know better: even if you think the general task is impossible to achieve, something simple could be achieved. and it could surprise you
that I mean: https://github.com/opencv/opencv
or others if you don't trust them
choose closer to you
no subject
Date: 2026-06-11 07:39 am (UTC)no subject
Date: 2026-06-11 07:40 am (UTC)no subject
Date: 2026-06-11 08:40 am (UTC)0822z ::ffff:80.234.76.107: at least we can try to intercept vision tract and use OpenCV to see what the other person sees
0823z ::ffff:80.234.76.107: or we can try to change what the other person sees
0823z ::ffff:80.234.76.107: I hope it is clear that it is not more complex then do that with the IP camera
0823z ::ffff:80.234.76.107: you just need RF front end that is possible to implement as it was shown
0824z ::ffff:80.234.76.107: tell it to RF engineers and machine learning ppl
0824z ::ffff:80.234.76.107: maybe other things may surprise you too
0833z ::ffff:80.234.76.107: if you think that the OpenCV of the vision tract is possible
0833z ::ffff:80.234.76.107: why not? you just need full-custom CMOS transiever with a lot of digital correlators.
0833z ::ffff:80.234.76.107: then you may be surpised that other thing are simpler to implement
0833z ::ffff:80.234.76.107: general inductive logic is just a finite state machine
0834z ::ffff:80.234.76.107: with a finite number of states
0834z ::ffff:80.234.76.107: at least you can try to check it
0834z ::ffff:80.234.76.107: maybe you will find that it is wrong
0837z ::ffff:80.234.76.107: because it may be connected to the quantum phusics itself
0839z ::ffff:80.234.76.107: but for vision you just need achivable RF front end
0839z ::ffff:80.234.76.107: and OpenCV
0839z ::ffff:80.234.76.107: you can start with the simple animals
0839z ::ffff:80.234.76.107: with a small number of neurons
no subject
Date: 2026-06-11 08:57 am (UTC)0852z ::ffff:80.234.76.107: https://transitional-writes.dreamwidth.org/44972.html?view=134572&posted=1#cmt134572
0852z ::ffff:80.234.76.107: https://transitional-writes.dreamwidth.org/44972.html
0855z ::ffff:80.234.76.107: 1. you can start with simple animals
0856z ::ffff:80.234.76.107: 2. but the ppl who I know did that experiments started with simple jokes with young fertile women
no subject
Date: 2026-06-11 09:20 am (UTC)0917z ::ffff:80.234.76.107: ppl try to think about. 1. intercept of the human brain impulses by the RF front end. 2. the task to recognize them by the things like OpenCV
0918z ::ffff:80.234.76.107: 1. first thing could be achieved. very low frequency waves could be received by the matched antenna. techniques like LTE beamforming and oversampling could be used to scan groups of neurons
0919z ::ffff:80.234.76.107: 2. this part is not different then that for IP cameras
0919z ::ffff:80.234.76.107: you can start with simple animals
0919z ::ffff:80.234.76.107: you can try to start with other simple tasks
0919z ::ffff:80.234.76.107: to move step by step from simple to more complex things