Uninterruptible 12VDC power supply! Powerful DC UPS module with maintenance-free Supercaps and wide-range input 16… 32VDC The robust DC2412-UPSDP2 is a maintenance-free 12VDC emergency power supply in open frame design. To protect against voltage fluctuations, flicker, voltage drops...

The SiglentSDG7000A Series of 2-channel AWGs offers models in maximum frequencies of 350MHz, 500MHz, and 1GHz, with 5Gsa/s sampling, 14-bit vertical resolution, and a memory depth of 512Mpts.  Arbitrary waveforms are generated with sample rates from 0.01Sa/s to 2.5GSa/s, and vector...

We have already come across tens if not hundreds of Raspberry Pi’s in-house silicon tapeout RP2040 integrated boards. The RP2040 was first seen in Raspberry Pi’s own microcontroller board– RPi Pico that features a dual-core Arm Cortex-M0+ processor with 264KB internal RAM and...

Last week, Codasip, known for edge tools and IPs, has announced RISC-V-based embedded cores for AI/ML edge customizations – L31 and L11 RISC-V processor cores. In addition to the existing low-power embedded cores, the L31 and L11 are aimed towards easing the customization process...

Even after the release of a 64-bit Raspberry Pi single-board computer, the Raspberry Pi OS remained with the 32-bit version– but in the making of a 64-bit OS. After a series of testing and validation from in-house engineers, while taking feedback from the community after the beta...

AI accelerators are specialized hardware designs that are built for computing complex AI workloads in the field of edge computing. While deep neural networks are assumed to be the optimized solution for image recognition and object detection, AI tasks, a group of researchers from the...

Axiomtek – a world-renowned leader relentlessly devoted in the research, development and manufacture of series of innovative and reliable industrial computer products of high efficiency – is proud to announce the CAPA55R, a high-performance 3.5” embedded SBC powered by the 11th...

Aspinity's analogML core features the improved capabilities of a tinyML chip with low-power analog neuromorphic computing architecture– with a system-level approach to low-power edge processing. Without making use of power-hungry digitization and digital processors, the analogML core...