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MAX78002GXE+

Name: Analog Devices Inc. MAX78002GXE+
Brand: Analog Devices / Maxim Integrated
SKU: 700-MAX78002GXE+
Price: 3088.43 THB
Availability: InStock

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Mouser No:

700-MAX78002GXE+

Mfr. No:

MAX78002GXE+

Mfr.:

Analog Devices / Maxim Integrated

Description:

ARM Microcontrollers - MCU ARM M4F w/ 2MB Weight CNN Accelerator, C

Datasheet:

MAX78002GXE+ Datasheet

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Product Attribute	Attribute Value	Select Attribute
Manufacturer:	Analog Devices Inc.
Product Category:	ARM Microcontrollers - MCU
RoHS:
Mounting Style:	SMD/SMT
Package/Case:	CSBGA-144
Core:	ARM Cortex M4F
Program Memory Size:	2.5 MB
Data Bus Width:	32 bit
Maximum Clock Frequency:	120 MHz
Number of I/Os:	60 I/O
Data RAM Size:	384 kB
Supply Voltage - Min:	2.85 V
Supply Voltage - Max:	3.6 V
Minimum Operating Temperature:	- 40 C
Maximum Operating Temperature:	+ 105 C
Packaging:	Tray
Analogue Supply Voltage:	1.71 V to 1.89 V
Brand:	Analog Devices / Maxim Integrated
Data RAM Type:	SRAM
Data ROM Size:	64 kB
Data ROM Type:	ROM
Interface Type:	I2S, SDIO
Moisture Sensitive:	Yes
Number of Timers/Counters:	3 Timer
Operating Supply Voltage:	2.85 V to 3.6 V
Processor Series:	MAX78002
Product:	MCUs
Product Type:	ARM Microcontrollers - MCU
Program Memory Type:	Flash
Factory Pack Quantity:	189
Subcategory:	Microcontrollers - MCU
Watchdog Timers:	Watchdog Timer

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MOUSER WILL NO LONGER BE CARRYING THIS ITEM IN THE FUTURE.

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Datasheet

MAX78002GXE+ Datasheet

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Compliance Codes

CAHTS:: 8542310000
USHTS:: 8542310025
ECCN:: 5A992.C

Origin Classifications

Country of Origin:: Taiwan
Assembly Country of Origin:: Not available
Country of Diffusion:: Not available

The country is subject to change at the time of shipment.

MAX78002 Artificial Intelligence Microcontrollers

Analog Devices MAX78002 Artificial Intelligence Microcontrollers are AI microcontrollers that enable neural networks. The Analog Devices MAX78002 can execute at ultra-low power and live at the edge of the IoT. The devices combine energy-efficient AI processing with ultra-low-power microcontrollers. This hardware-based CNN accelerator enables battery-powered applications to execute AI inferences while expending only millijoules of energy.