Arm’s ARMv8.1-M architecture specification redefines its microcontroller offerings (Fig. 1). It includes the company’s Helium technology, which addresses machine-learning (ML) applications. Arm ...

I am in the process of updating my book "Electronics Explained," published by Newnes/Elsevier. The book is essentially a basic electronics text for those learning about electronics for the first time.

Well, there's always something unexpected going on here in the Pleasure Dome (my office). Just a few days ago, for example, I received an email from author and lecturer Don Wilcher … Don explained ...

STMicroelectronics (NYSE:STM) is ready to launch its new series of microcontrollers with machine learning capabilities in high volumes. The Switzerland-based company said the STM32N6 microcontroller, ...

CMSIS-NN is an open-source library of optimized software kernels that maximize NN performance on Cortex-M cores with minimal memory footprint overhead. Machine learning (ML) algorithms are moving to ...

TAINAN, Taiwan, June 30, 2020 (GLOBE NEWSWIRE) -- Himax Technologies, Inc. (Nasdaq: HIMX) (“Himax” or “Company”), a leading supplier and fabless manufacturer of display drivers and other semiconductor ...

TOKYO--(BUSINESS WIRE)--Renesas Electronics Corporation (TSE:6723), a premier supplier of advanced semiconductor solutions, today announced the qualification of their RX65N Group of microcontrollers ...

As a result, this project is set up as a how-to for others looking to dive further into the world of microcontrollers that don’t have the same hand-holding setup as the Arduino. To take care of the ...

What’s the best way to learn electronics? It’s a pithy question to ask a Hackaday audience, most of whom are at least conversant in the field already. Those who already have learned often have just ...

Comprehensive and efficient facility management functions characterize the smart buildings that are a vital part of smart grids. These buildings use a digital network to connect and control a wide ...

Machine learning (ML) algorithms are moving to the IoT edge due to various considerations such as latency, power consumption, cost, network bandwidth, reliability, privacy and security. Hence, there ...