Has the Software Defined Radio Academy 2026 conference been cancelled?

Not strictly related to GNU Radio, but I was wondering if anyone knows if the Software Defined Radio Academy 2026 has been cancelled.

 

It used to take place during the Ham Radio exhibition in Friedrichshafen, Germany, so in theory it would have been next Saturday June 26, but when I tried to Google it, I didn't see any results, the website for the Ham Radio exhibition in Friedrichshafen doesn't seem to mention it, and the site for the SDRA26 (https://2026.sdra.io) seems to be down.

 

I found the presentations at previous SDRAs very interesting and of very high quality, so if it has been cancelled, I'll definitely miss it.

 

73,

Franco K4VZ

 

 

Re: ATSC 1.0 transmit errors

I'm not familiar with where things are installed on Windows, but you should have an already complete example flow graph named uhd_atsc_tx.grc somewhere.

It's probably in a directory with a name like gnuradio/share/gnuradio/examples/dtv

Also, the test file is https://www.w6rz.net/advastc.ts (which is noted in the example flow graph).

adv16apsk910.ts is the DVB-S2 test file and will still mostly work, but there will be either video of audio hiccups because it's the incorrect Transport Stream bitrate.

Ron

On 6/18/26 15:49, Kathy King wrote:

Hello

 I am using GNU radio companion 3.10.12.0, python 3.12.9.

I installed the windows version on a windows 10 computer.

 

I implemented the ATSC transmitter example from wikipedia.

I have three errors. They are all links between blocks and I have no

idea why they are erroring.

 

The first is the link path between the FILE SOURCE block and the ATSC PAD.

 

The second is the link path between ATSC FIELD SYNC MUX block and 

the VECTOR TO STREAM.

 

The third is the link path between KEEP M IN N block and DVB-S2X MODULATOR.

 

I am using adv16apsk910.ts as the file source.

I hope someone has the answer for me.

Mike

ATSC 1.0 transmit errors

Hello

 I am using GNU radio companion 3.10.12.0, python 3.12.9.

I installed the windows version on a windows 10 computer.

 

I implemented the ATSC transmitter example from wikipedia.

I have three errors. They are all links between blocks and I have no

idea why they are erroring.

 

The first is the link path between the FILE SOURCE block and the ATSC PAD.

 

The second is the link path between ATSC FIELD SYNC MUX block and 

the VECTOR TO STREAM.

 

The third is the link path between KEEP M IN N block and DVB-S2X MODULATOR.

 

I am using adv16apsk910.ts as the file source.

I hope someone has the answer for me.

Mike

GRCon26 CfP deadline extended to 2026-06-26 (was: GRCon26 - Abstracts due by June 13 - THIS WEEK!)

Hi everyone who's forgot to submit in time, please remember to submit your abstract before the 26th. Best, Marcus On 2026-06-10 2:55 PM, Josh Morman (GNU Radio) wrote: > Just a reminder that *GRCon26* (21-24 Sept 2026, Raleigh, NC) *Call for Participation > closes**June 13*.  Please submit abstracts in time for consideration. > > https://events.gnuradio.org/event/28/abstracts/ <https://events.gnuradio.org/event/28/ > abstracts/> > > All event information can be found here: https://events.gnuradio.org/event/28/ <https:// > events.gnuradio.org/event/28/> > > If you have any questions, please don't hesitate to contact us - grcon@gnuradio.org > <mailto:grcon@gnuradio.org>. > > Looking forward to seeing all of you in Raleigh in September!! > > Josh >

Simple RF control application for the gnu radio and AI researchers

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.

You can start with that.

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 is is very small.

And the real algorithmic complexity of human brain is relatively low.

https://transitional-writes.dreamwidth.org/44972.html

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

Kirill Abramovich
Samara, Russia
wieker@gmail.com

GRCon26 - Abstracts due by June 13 - THIS WEEK!

Just a reminder that GRCon26 (21-24 Sept 2026, Raleigh, NC) Call for Participation closes June 13.  Please submit abstracts in time for consideration.

https://events.gnuradio.org/event/28/abstracts/

All event information can be found here: https://events.gnuradio.org/event/28/

If you have any questions, please don't hesitate to contact us - grcon@gnuradio.org.

Looking forward to seeing all of you in Raleigh in September!!

Josh

Hi, can we discuss possible Solomonoff induction flow for radio engineers?

Hi,

can we at least discuss the following thing:

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

See here more:

https://transitional-writes.dreamwidth.org/44972.html

Kirill Abramovich

Samara, Russia

wieker@gmail.com

wieker0@yandex.ru