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Name: LFE3-70EA-7LFN672C
Brand: Lattice Semiconductor Corporation
SKU: LFE3-70EA-7LFN672C
Price: 2.40 USD
Availability: InStock
Rating: 5 (2 reviews)

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Lattice Semiconductor Corporation LFE3-70EA-7LFN672C

Part No.:: LFE3-70EA-7LFN672C

Manufacturer:: Lattice Semiconductor Corporation

Package:: 672-BBGA

Datasheet:: LFE3-70EA-7LFN672C.pdf

Description:: IC FPGA 380 I/O 672FPBGA

In Stock:: 2163

Quantity:: Add To Cart

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LFE3-70EA-7LFN672C Specifications

Package/Case:
672-BBGA
Packaging:
Tray
Series:
ECP3
ProductStatus:
Active
NumberofLABs/CLBs:
8375
NumberofLogicElements/Cells:
67000
TotalRAMBits:
4526080
NumberofI/O:
380
NumberofGates:
-
Voltage-Supply:
1.14V ~ 1.26V
MountingType:
Surface Mount
OperatingTemperature:
0°C ~ 85°C (TJ)

LFE3-70EA-7LFN672C this integrated circuit is available in factory sealed anti static packs. at icwhale.com. Please read product page below detail information. including LFE3-70EA-7LFN672C price, data-sheet, in-stock availability, technical difficulties. Also. Quickly Enter the access of compare listing to find out replaceable electronic parts. If you want to retrieve comprehensive data for LFE3-70EA-7LFN672C to optimize the supply chain (including cross references, life-cycle, parametric, counterfeit risk, obsolescence managements forecasts), please contact to our Tech-supports team.

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LFE3-70EA-7LFN672C information

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LFE3-70EA-7LFN672C application case analysis in emerging technology fields

LFE3-70EA-7LFN672C is a field-programmable gate array (FPGA) with advanced features, ideal for a wide range of applications requiring high-performance computing and flexibility in design.

Application Scenario:

In autonomous vehicles, LFE3-70EA-7LFN672C can be utilized to enhance perception and decision-making capabilities, enabling intelligent navigation and real-time response to changing road conditions.

System Architecture:

To implement autonomous driving using LFE3-70EA-7LFN672C, the following architectural components can be considered:

1. Sensor Fusion:

Integrate various sensors, such as LiDAR, radar, and cameras, to capture comprehensive environmental data. Use the programmable logic resources of LFE3-70EA-7LFN672C to perform sensor fusion algorithms, combining data from different sources to create a unified perception of the vehicle's surroundings.

2. Machine Learning Acceleration:

Utilize the embedded DSP blocks and programmable fabric of LFE3-70EA-7LFN672C to accelerate machine learning algorithms for object detection, classification, and trajectory prediction. This enables the vehicle to recognize and respond to various objects and obstacles in real-time.

3. Decision Making:

Implement decision-making logic using the configurable logic elements (CLEs) and embedded processors of LFE3-70EA-7LFN672C. Develop algorithms for path planning, obstacle avoidance, and vehicle control, considering factors such as traffic rules, road conditions, and navigation objectives.

4. Real-Time Communication:

Enable communication with external systems, such as GPS receivers and V2X (vehicle-to-everything) infrastructure, using the high-speed transceivers and serial interfaces available in LFE3-70EA-7LFN672C. This facilitates seamless integration with navigation services and vehicle-to-infrastructure communication for enhanced situational awareness.

5. Power Efficiency:

Optimize power consumption by utilizing the low-power features and dynamic power management capabilities of LFE3-70EA-7LFN672C. Implement power gating techniques and clock gating strategies to minimize energy consumption while maintaining responsive performance.

Considerations:

When designing the autonomous driving system, it's essential to consider:

- Safety and Redundancy: Implement redundant systems and fail-safe mechanisms to ensure safe operation in critical situations.

- Regulatory Compliance: Adhere to relevant safety standards and regulations for autonomous vehicles, ensuring compliance with requirements for functional safety and reliability.

- Validation and Testing: Conduct rigorous testing and validation procedures to verify the performance and reliability of the autonomous driving system under various operating conditions and scenarios.

- Scalability and Upgradability: Design the system architecture to be scalable and easily upgradable, allowing for future enhancements and integration of new technologies as they become available.

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6. What is the process for return or replacement of LFE3-70EA-7LFN672C?

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(1)Such as a deficiency in quantity, delivery of wrong items, and apparent external defects (breakage and rust, etc.), and we acknowledge such problems.

(2)We are informed of the defect described above within 90 days after the delivery of LFE3-70EA-7LFN672C.

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