Expert Insights - Embedded

Scot Morrison  |  April 30, 2020

Delivering on security for Linux-based medical devices

How should you address the monitoring and resource challenges in maintaining security for Linux devices.
Colin Walls  |  February 7, 2020

Choosing an embedded operating system

You cannot break your operating system choice down in something as simple as a flowchart but there are some headline criteria you should think about.
Jean-Marie Brunet and Lauro Rizzatti  |  December 17, 2019

System-of-systems validation for automotive design

How Siemens PAVE 360 platform leverages emulation to deliver the exhaustive test required for the incoming generation of autonomous vehicles.
Colin Walls  |  December 10, 2019

Self-test strategies for embedded systems

How to implement self-test across the four main areas where embedded systems can fail.
Topics: Embedded - Integration & Debug  |  Tags: , , , , ,   |  Organizations:   |  
Puneet Sinha  |  November 29, 2019

Vehicle autonomy and electrification: a perfect match

Is it worth building sophisticated autonomous driving systems if their power consumption reduces an electric vehicle's range? Maybe yes.
Paul Dempsey  |  June 18, 2019

The vocal persuader

In conversation with author and SEMICON West/ES Design West keynoter Bob Pearson on the challenges facing tech on external and internal communication.
Bob Smith  |  March 15, 2019

Enabling the move to a system-centric view

Bob Smith of the ESD Alliance describes how we can promote the ongoing evolution of the design ecosystem.
Morten Christiansen  |  November 5, 2018

Understanding USB 3.2 and Type-C

The basics of USB 3.2, how to implement it in an SoC, and how USB Type-C connectors and cables are used in USB 3.2 systems.
Topics: Embedded - Architecture & Design, IP - Selection  |  Tags: , ,   |  Organizations:   |  
Allen Watson  |  October 3, 2018

An open-source framework for greater flexibility in machine-learning development

Exchange frameworks are emerging to make it easier for neural-network developers to swap between development environments.
Gordon Cooper  |  September 23, 2018

Flexible embedded vision processing architectures for machine-learning applications

Machine-learning strategies for embedded vision are evolving so quickly that designers need access to flexible, heterogenous processor architectures that can adapt as the algorithms evolve.
Topics: Embedded - Architecture & Design, IP - Selection  |  Tags: , ,   |  Organizations:   |  

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