AIR-T Edge Series – The Only Rugged Software Defined Radio with a GPU Artificial intelligence (AI) technology has significantly enhanced capability within computer vision, speech recognition, cybersecurity, and robotics. In parallel, demands on performance in radio frequency (RF) systems have become increasingly more complex while simultaneously requiring higher data rates. The next generation of wireless […]
How to Deploy a MATLAB Deep Learning Model on the AIR-T Deepwave Digital has included support for MATLAB and the Deep Learning Toolbox using the Open Neural Network Exchange (ONNX) to our artificial intelligence (AI) training-to-deployment workflow toolbox for the AIR-T. MATLAB is the tool of choice for high-productivity research, development, and analysis across many […]
AirStack 0.4.2 31 March 2021 The Deepwave Digital team is happy to announce the release of AirStack 0.4.2, a minor release that resolves a few bugs. This upgrade may be performed in minutes without re-imaging the AIR-T system. Bug Fixes Remove extraneous kernel log messages that would be generated during normal operation of […]
AirStack 0.4.1 23 October 2020 The Deepwave Digital team is announcing AirStack 0.4.1, a minor release that resolves a few bugs and improves performance. This upgrade may be performed in minutes without re-imaging the AIR-T system. New Features Transceiver Temperature Sensor – The temperature sensor found on the AD9371 can now be accessed […]
Deepwave has added support for PyTorch and Open Neural Network Exchange (ONNX) to our artificial intelligence (AI) training-to-deployment workflow toolbox for the AIR-T. PyTorch is the fastest growning training framework in AI and deep neural networks (DNN). ONNX is the industry open standard for saving, distributing, and deploying AI and DNN solutions in an interoperatable […]
Firmware Development Kit for the AIR-T AirStack Sandbox is the new FPGA development kit for customers to deploy their own intellectual property (IP) on the AIR-T’s FPGA. The Deepwave team has worked tirelessly to abstract away all of the complications of writing custom firmware and has now enabled our customers to interact with the […]
AirStack 0.4.0 27 August 2020 The Deepwave Digital team is proud to announce that AirStack Version 0.4.0 is now available for download to AIR-T customers. Revision 0.4.0 of AirStack saw a number of changes and additional features designed to better support the underlying hardware and to make upgrades easier in the future. We […]
Deepwave Digital has just released a comprehensive workflow toolbox for creating, training, optimizing, and deploying a neural network on the AIR-T. This new deployment toolbox works natively on the AIR-T and AirStack without the need to install any new packages or applications. This means that the workflow for an AI enabled radio frequency (RF) […]
Deepwave Digital is happy to announce that a new model for the AIR-T Embedded Series is now available on our website. The AIR7201 has 4x more FPGA resources allowing for the deployment of more complex signal processing and deep learning applications on the AIR-T. This increased compute power may be leveraged for pre-processing of […]
We are excited to announce that AirStack Version 0.3.0 is now available for download in the Developer Portal for the AIR-T. The Deepwave team has been working very hard to bring this update to the community and believe that these new features will allow customers to create new and exciting applications for deep learning […]
Deepwave Digital is excited to announce that we have expanded our distributors to include Arrow Electronics. Arrow is fully stocked and selling the Artificial Intelligence Radio Tranceiver. The following models are available for sale at Arrow’s website: Artifical Intelligence Radio Tranceiver (AIR-T) AIR7101-A | – Artifical Intelligence Radio Tranceiver (AIR-T) The AIR7101-A is a high-performance […]
Webinar: Detecting and Labeling Training Data for Signal Classification Update The video stream, slides, and source code are now available to the general public. Slides You may download the slides here. Video Stream Source Code Available in the webinar section of our GitHub here. Original Post Deep Learning Series Part 1 […]
Deepwave and RAPIDS Team Collaborate on cuSignal 0.13 Over the past few months NVIDIA has been working on a new version of cuSignal: version 0.13. As part of their RAPIDS environment, cuSignal GPU accelerates all of the signal processing functions in the SciPy Signal Library. Read the Medium full article here. Online Processing Deepwave has […]
Deepwave Digital Webinar Update The webinar on March 25, 2020 was a great success and we thank you for attending! The video stream, slides, and source code are now available to the general public. Slides You may download the slides here. Video Stream Source Code Available in the new webinar section of our […]
Power Spectrum Measurement If you are looking for a very simple way to acquire the power spectral density of a received signal with the AIR-T, you may like the Soapy Power Project. The resulting spectrum output may be used for monitoring interference, acquiring signals for deep learning, or for examining a test signal. Soapy Power […]
06 December 2019 Major Upgrades to the AIR-T The Deepwave Digital team is proud to announce that AirStack Version 0.2.0 is now available for download to AIR-T customers. Revision 0.2.0 of AirStack saw a number of changes and additional features designed to better support the underlying hardware and to make upgrades easier in […]
Deepwave’s AIR-T Shows Viability as CBRS Sensor Deepwave Digital is proud to announce that their sensor has concluded certification testing to become a critical component in the 5G Citizens Broadband Radio Service (CBRS) network: the first commercial spectrum sharing network. The Deepwave team has implemented a deep neural network on their Artificial Intelligence Radio Transceiver […]
End-to-End Signal Processing and Deep Learning Using Embedded GPUs The following presentation was given at NVIDIA’s GPU Technology Conference (GTC) in Washington, DC on November 5, 2019. It was a great event where technology was showcased from many different research areas. Presenter Daniel Bryant Abstract We’ll present the GPU-accelerated digital signal processing (DSP) applications enabled […]
The Premier AI Event is back in DC "The center of the AI ecosystem shifts to D.C. this fall, when the GPU Technology Conference arrives at the Reagan Center in Washington, from Nov. 4-6." Check out the full NVIDIA Blog post here. The GTC DC event is a top-tier AI conference directed towards government, defense, […]
Overview This tutorial will teach you how to integrate GPU processing using CUDA with GNU Radio on the AIR-T software defined radio. Once completed, you will be able to build a custom GPU processing block within GNU Radio and use it to process your own signals. The tutorial assumes some familiarity in programming in Python […]
FFTs with CUDA on the AIR-T with GNU Radio GPUs are extremely well suited for processes that are highly parallel. The Fast Fourier Transform (FFT) is one of the most common techniques in signal processing and happens to be a highly parallel algorithm. In this blog post the Deepwave team walks you though how to […]
AIR-T Enclosures Fresh off the Production Line We have just received our first production versions of the new AIR-T software defined radio enclosure and it is beautiful. If you already have and AIR-T, you can order a kit today to protect your SDR. If you are thinking about acquiring our GPU enabled SDR, make sure […]
Title: Simplifying AI for Communications, Radar, and Wireless Systems Presented by John Ferguson (CEO Deepwave Digital) Abstract Radio frequency (RF) systems have become increasingly complex, and the number of connected devices is expected to increase. We’ll discuss how deep learning within RF shows promise for dealing with a congested spectrum by enhancing reliability and simplifying […]
Deepwave Digital directly enables the incorporation of artificial intelligence (AI) in radio frequency (RF) and wireless systems by supplying customers an integrated hardware and software solution. Our technology moves the AI computation engine to the signal edge of the RF system to reduce network bandwidth, latency, and human-driven analysis requirements.