I used to work with EW and have always thought that training Akida to recognise the different emitters (which are basically signals emitted to be repelled back of the different surfaces of particular military hardware to categorise that hardware by the signal returned) would be a bread and butter use case for Akida - which we know is particularly good at understanding RF and then also be able to learn new emitters it hasn’t been trained for in the field. This would change the way military reconnaissance is being performed and make the process a whole lot easier to keep up to date.
Agree, RF could be an interesting one.
Not just military but also Lidar amongst others.
I saw
@Fact Finder earlier post discussing 16nm as well as Xilinx.
From Nandans tweet I decided to have a closer look at Ipsolon Research as he provided a web link. One of the companies he thanked re Akida Gen 2.
Was curious where they fit into picture.
So, snip of Ipsolon.
We want you to be an innovator, too. Our engineering and production is done on-site so we can be trusted partners by providing fully-customized, leading-edge, timely technology solutions.
www.ipsolonresearch.com
Ipsolon Research is an innovator in software defined radio technology.
We launched Ipsolon Research in 2017 to develop and improve the analog and digital signal processing system for an airborne obstruction penetrating LIDAR system. Since then, we’ve engineered hardware, software, and FPGA design for a range of Software Defined Radios (SDR) and advanced wireless systems.
In addition to work for commercial wireless IC, we also manufacture and sell Chameleon and Cerberus Radios, both are wideband, small-form factor SDR for military communications, anti-jamming, and other advanced wireless signal processing applications. Our goal is to provide the wireless community with advanced radio system software and hardware development, early SDR conceptual design, advanced signal processing, and rapid prototyping.
From Ipsolon product page...16nm Xilinx.
They have a new product due soon but doesn't give specs yet.
ARAGMA
Coming soon!
www.ipsolonresearch.com
DIGITAL SIGNAL PROCESSING HORSEPOWER
16 TX/RX Channels, Smallest Footprint Software Defined Radio/RADAR
Multi-processor Subsystem
- Xilinx 16nm FinFET RFSoC XCZU29
- Quad-core 1.2 GHz ARM Cortex-A53 64b with L1/L2, MMU, DMA
- Dual 500MHz R5 real-time processor, power manager & secure boot
- 4GB DDR4, Micro SD memory
- Range of IO including UARTs, 1G Ethernet, USB3.0
- Massive parallel AXI IO between PS and FPGA fabric
FPGA Resources
- 30+ system logic cells (K), 16 32g SERDES
- 4,272 DSP slices, 2.13 TMACs @ 500 Mhz
Ipsolon also connected with US Navy via SBIR in 2021.
Frederick, MD – The United States Navy has selected Ipsolon Research’s SBIR for a phase II follow-on contract after a successful phase I demonstration of its Deep Learning (DL) techniques. “We used DL techniques to replace or extend the PDW-based approach to radar signal detection, “explained...
www.ipsolonresearch.com
Ipsolon Research wins follow-on contract with Navy
September 9, 2021
Fredrick, MD – The United States Navy has selected Ipsolon Research’s SBIR for a phase II follow-on contract after a successful phase I demonstration of its Deep Learning (DL) techniques.
“We used DL techniques to replace or extend the PDW-based approach to radar signal detection, “explained Ipsolon Research CEO, John Shanton.
Deep learning (DL) algorithms are a form of Machine Learning (ML) that use neural network (NN) architectures to process data and predict the presence of data patterns often called prediction or inference.
The specific goal of this project is to develop a deployable electronic sensor optimized to use ML techniques for real-time detection of radar signals and other signals of interest.
“The phase I results demonstrated that ML is a viable method for detection of a known radar signal type in power- and space-efficient FPGA devices,” Shanton said.
Was reading an article from 2020 about..
Artificial Intelligence in Radio Frequencies
Artificial intelligence (AI) and machine learning (ML) as an application of AI, has today become an inevitable part of major industries such as healthcare, financial trending, and transportation. Future urgent need to intelligently utilize wireless resources to meet the need of ever-increasing...
signalprocessingsociety.org
Excerpt.
Application of Machine Learning in Cognitive Radio
The concept of CR was first proposed by Joseph Mitola [
1] in order for mitigating the scarcity in limited radio spectrum by improving spectrum allocation efficiency by allowing unlicensed users (cognitive radio users) to identify and transmit over the frequency bands which are already assigned to the licensed users (primary users), but idle over specific time/space (spectrum holes). Spectrum hole identification is usually achieved by sensing the radio frequency (RF) environment through a process called spectrum sensing. It should be noted that the title of CR is not limited only to unlicensed wireless users and implied to any wireless user that adds the cognition capability along with reconfigurability to its system function.
So, where had I heard of "cognitive radio"?...oh that's right...from the Ph I and Ph II NASA solicitation with Intellisense using Akida.
So some prev posts on NECR and related SBIRs as refresh.
I wonder if they'll find any cheese there? 🧀 https://www.dailymail.co.uk/sciencetech/article-10889589/NASA-launch-priority-mission-explore-mysterious-domes-moon.html Just some Gromit droppings.😁
thestockexchange.com.au
I would think of the C4 was horrible then We would have had it out on the Friday to forget it over the weekend plus the market a are strong . That said I'm not saying it be stellar but I think is will be reasonable revenue released next week imo. Hoping to see over a million to 2 million.
thestockexchange.com.au
They have mastered the art of capping the BRN share price even on the greenest days. Be lucky to finish the day green.
thestockexchange.com.au
