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MAX78002GXE+

Name: Analog Devices Inc. MAX78002GXE+
Brand: Analog Devices / Maxim Integrated
SKU: 700-MAX78002GXE+
Price: 532.49 DKK
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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In Stock: 101

Stock:: 101 Can Dispatch Immediately

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Factory Lead Time:: 10 Weeks Estimated factory production time for quantities greater than shown.

Quantities greater than 101 will be subject to minimum order requirements.

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Pricing (DKK)

Qty.	Unit Price	Ext. Price
	532,49 kr.	532,49 kr.
	442,53 kr.	4.425,30 kr.
	421,27 kr.	10.531,75 kr.
	395,60 kr.	39.560,00 kr.
	383,74 kr.	72.526,86 kr.

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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
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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Datasheet

MAX78002GXE+ Datasheet

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TARIC:: 8542319000
CAHTS:: 8542310000
USHTS:: 8542310025
ECCN:: 5A992.C

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.