This launch introduces our Smart Card Trust Provisioning Solution, bringing customers a major new capability in protecting their Software Intellectual Property (IP) and guarding against over-production and cloning.
Hooking up to the external world usually means that our MCUs must learn to “speak” analog. A high-performance analog system was added to the LPC553x family to enable more integrated, lower external component count designs.
NXP's free UI design tool for the open source LVGL graphics library continues to add great new features and capabilities. GUI Guider 1.3.0 was released on January 24th 2022 and includes exciting new widgets, more host platform support, Keil project output and Micropython.
After setting my new 16” M1Max Macbook Pro, I found some surprising results for the kernel compile time. The Ubuntu Virtual Machine on my M1 MBP compiled the i.MX Linux kernel faster than an Intel i9 3650 Dell Precision workstation running native Ubuntu. Since the comparison is a bit like apple to oranges, I tried to minimize the variables, and, I also compared an older i7 Dell Precision M4700 and a Xeon.
NXP has now introduced MCU-Link Pro - the second incarnation of the MCU-Link debug probe architecture, adding several powerful capabilities and features to build on the entry level MCU-Link standalone model. This includes power/energy measurement, USB bridging and a J-Link firmware option.
NXP has released a new library, replacing LPCUSBSIO, to enable communication via USB bridges available on evaluation boards with LPC-Link2 and upcoming MCU-Link probes. User documentation and a Python wrapper are also available.
An interactive tutorial on how to create your own MATLAB Simulink temperature sensor application by applying the model-based design approach, how to configure and use the i.MXRT1060 EVK using NXP MCUXpresso, a thermistor module and the IMXRT Toolbox.
NXP's innovative MCUs, based on Arm® Cortex®-M cores and part of the EdgeVerse™ edge computing platform, continue to transform the industry landscape with increasing performance and integration, further complemented by outstanding enablement including MCUXpresso software and tools and an extensive ecosystem of partners. Get started now!
PyeIQ is written on top of eIQ™ ML Software Development Environment and provides a set of Python classes allowing the user to run Machine Learning applications in a simplified and efficiently way without spending time on cross-compilations, deployments or reading extensive guides.
Now PyeIQ 3.0.x release is announced. This release is based on i.MX Linux BSP 5.4.70_2.3.0 & 5.4.70_2.3.2(8QM, 8M Plus) and can also work on i.MX Linux BSP 5.10.9_1.0.0 & 5.10.35_2.0.0 & 5.10.52_2.1.0. And also, in latest PyeIQ 3.1.0 release, BSP 5.10.72_2.2.0 is also added into supported list.
This article is a simple guide for users. For further questions, please post a comment on eIQ Community or just below this article.
In my previous twoarticles, we examined the core components to an RT600 hardware design using the code name “Super-Monkey”. The objective of the Super-Monkey project to produce minimal configuration design example using RT685 audio crossover MCU that would support my real-time audio processing projects. There is quite a bit IO available on the RT685, but I chose to constrain my design to the most common functions for real-time audio. My applications generally use professional, “flagship quality” audio codecs for musical instrument signal processing. Using this as a guide, the process of coming up with a minimal IO complement was simplified. It is time to now time reveal the Super-Monkey design!
This article will continue detailing a minimal configuration design that uses an i.MX RT685 crossover MCU. In the first article of this hardware design series, I introduced the power supply architecture of the RT600 series and illustrated some of the package/PCB layout features of the VFBGA176 package. I also introduced some of the specs I am working towards for the “Super-Monkey” module and will power some of my future real-time audio processing projects.
As a real-world example, I this article is part one of several articles that will step through a basic RT600 hardware design and bring-up. I find this to be a very useful exercise as high-end MCU’s can be overwhelming, especially to those coming from a traditional MCU background. The goal here is to develop a simple “minimal configuration” example and build it for a demonstration.
The Local Interconnect Network (LIN) was developed as a complementally bus standard to the Controller Area Network (CAN bus) to address the need for a cost-efficient network for lower performance devices within the vehicle. While the CAN network was already in place within vehicles, its high bandwidth and advanced error detection capabilities were overkill (and thus, cost-prohibitive) for lower performance applications such as seat and window controllers.
In Part 1 of our introduction to the RT600 crossover MCU, we examined the RT600 CPU/DSP core complex and its unique system memory architecture. In part 2, we will put a spotlight on some other unique peripheral features that make the RT600 standout as a high-performance audio crossover MCU.
This article is the first part of a two part series focusing in on one of the newer members of the i.MX RT crossover family: the RT600. The RT600 crossover MCUs are focused on real-time number crunching applications such as audio, sensor fusion and machine learning.
CAN FD is an extension to the Classic CAN protocol that was developed to meet the needs of modern vehicles wherever-increasing numbers of embedded electronics are transmitting ever-increasing amounts of control and diagnostic data. Because the original CAN specification has a maximum bandwidth limitation of 1 Mbps, data-dense activities like ECU flashing and advanced driver assistance systems (ADAS) ADAS applications were being impeded, forcing automotive manufacturers to add multiple CAN networks into newer vehicles.