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STM32L562E-DK

Name: STMicroelectronics STM32L562E-DK
Brand: STMicroelectronics
SKU: 511-STM32L562E-DK
Price: 119.83 CAD
Availability: InStock

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Mouser #:

511-STM32L562E-DK

Mfr. #:

STM32L562E-DK

Mfr.:

STMicroelectronics

Description:

Development Boards & Kits - ARM Discovery kit with STM32L562QE MCU

Complete Your Design

Datasheet:

STM32L562E-DK Datasheet (PDF)

More Information

Learn more about STMicroelectronics STM32L562E-DK

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Pricing (CAD)

Qty.	Unit Price	Ext. Price
	$119.83	$119.83

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Product Attribute	Attribute Value	Select Attribute
Manufacturer:	STMicroelectronics
Product Category:	Development Boards & Kits - ARM
Shipping Restrictions:	This product may require additional documentation to export from the United States.
RoHS:
Product:	Discovery Kits
Core:	ARM Cortex M33
Tool Is For Evaluation Of:	STM32L562E
Packaging:	Bulk
Brand:	STMicroelectronics
Interface Type:	USB
Product Type:	Development Boards & Kits - ARM
Factory Pack Quantity:	1
Subcategory:	Development Tools
Unit Weight:	124 g

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Datasheet

STM32L562E-DK Datasheet (PDF)

CNHTS:: 8543709990
USHTS:: 8471500150
ECCN:: 5A002.A.4

STM32L562E-DK Discovery Kit

STMicroelectronics STM32L562E-DK Discovery Kit is a full-featured demonstration and development platform for the Arm® Cortex®-M33 with TrustZone® and ARMv8-M mainline security extension core-based STM32L562QE Microcontroller, with 512KB of Flash memory and 256KB of SRAM. The STM32L562E-DK Discovery kit from STMicroelectronics makes use of the STM32L562QE MCU's innovative ultra-low-power oriented features to enable prototyping for many wearable or sensor applications, with state-of-the-art energy efficiency, secure boot, and TrustZone-based software isolation.

NanoEdge™ AI Studio

STMicroelectronics NanoEdge™ AI Studio is a Machine Learning (ML) technology to bring true innovation easily to the end-users. In just a few steps, developers can create an optimal AI library for a project based on minimal data and with no specific data science skills. Smarter products will detect environment anomalies, classify signal patterns and anticipate behaviors due to optimized algorithms generated from a simple PC-based GUI.