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Technology Days - Training Material

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Automotive

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Secure designs begin with a security model consisting of policies, an understanding of the threat landscape and the methods used to enforce physical and logical security. To protect firmware execution given today’s threat landscape, there must be a policy to only allow execution of authenticated firmware. The methods used to enforce this policy rely on MCU security technology to create a protected boot flow. The boot firmware can contain public key cryptography to authenticate application code. In addition to these components integrated in the end device, there are tools and steps that must be taken in the manufacturing environment using manufacturing hardware for code signing and host programs for provisioning. Join this session to explore the design and implementation of a secure boot by making use of the Arm mbed TLS open source software and protect against firmware attacks.
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This class will teach you how to spin a BLDC, PMSM or ACIM motor with i.MX RT. You do not need prior motor control experience.
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Hands-on starting with the i.MX 8M Mini EVK, we will cover the out-of-the-box enablement including software, tools, hardware design guides, and demonstration software. Attendees should leave this class with the confidence to start their own design using the i.MX 8M Mini.
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Machine learning can performed on a wide range of device categories - from MCUs with Arm® Cortex®-M4 and M7 cores to complex SoCs with high-end A-class cores, GPUs, DSPs, and dedicated machine learning accelerators. The first step is learning how to utilize proper training techniques for model development, but beyond that how to generate optimized inference engines that can be used to perform classifications, anomaly detection, predictions, and other types of decisions. This presentation highlights some basic training techniques, such as data augmentation, but the primary focus will be on various ways to deploy neural network frameworks and classical machine learning algorithms, and most importantly, utilizing a variety of open source tools and techniques. We will show how these techniques fit in with some real use cases such as object recognition and anomaly detection.
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