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Name: LFE2M35E-7FN484C
Brand: Lattice Semiconductor Corporation
SKU: LFE2M35E-7FN484C
Price: 2.40 USD
Availability: InStock
Rating: 5 (2 reviews)

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Lattice Semiconductor Corporation LFE2M35E-7FN484C

Part No.:: LFE2M35E-7FN484C

Manufacturer:: Lattice Semiconductor Corporation

Package:: 484-BBGA

Datasheet:: LFE2M35E-7FN484C.pdf

Description:: IC FPGA 303 I/O 484FBGA

In Stock:: 2232

Quantity:: Add To Cart

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LFE2M35E-7FN484C Specifications

Package/Case:
484-BBGA
Packaging:
Tray
Series:
ECP2M
ProductStatus:
Active
NumberofLABs/CLBs:
4250
NumberofLogicElements/Cells:
34000
TotalRAMBits:
2151424
NumberofI/O:
303
NumberofGates:
-
Voltage-Supply:
1.14V ~ 1.26V
MountingType:
Surface Mount
OperatingTemperature:
0°C ~ 85°C (TJ)

LFE2M35E-7FN484C this integrated circuit is available in factory sealed anti static packs. at icwhale.com. Please read product page below detail information. including LFE2M35E-7FN484C 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 LFE2M35E-7FN484C 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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LFE2M35E-7FN484C information

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LFE2M35E-7FN484C application case analysis in emerging technology fields

LFE2M35E-7FN484C is a field-programmable gate array (FPGA) device known for its high performance and versatility, suitable for a wide range of applications requiring customizable hardware acceleration and processing capabilities.

Application Scenario:

In the field of image processing and computer vision, LFE2M35E-7FN484C can be effectively utilized to accelerate tasks such as object detection, image segmentation, and feature extraction.

System Architecture:

To leverage the capabilities of LFE2M35E-7FN484C for image processing applications, the system can be designed as follows:

1. Image Acquisition:

Capture images using sensors such as cameras or image sensors. Interface these sensors with the FPGA through appropriate interfaces like MIPI CSI or LVDS to transfer image data efficiently.

2. Image Preprocessing:

Implement preprocessing algorithms directly on the FPGA to enhance image quality, remove noise, and perform tasks such as color space conversion and image resizing. Utilize the parallel processing capability of LFE2M35E-7FN484C to accelerate these tasks.

3. Feature Extraction:

Utilize FPGA resources to extract features from images using techniques like convolutional neural networks (CNNs) or edge detection algorithms. Implement these algorithms efficiently using the FPGA's logic resources and dedicated DSP blocks.

4. Object Detection and Recognition:

Deploy trained models or custom algorithms on LFE2M35E-7FN484C to perform real-time object detection and recognition tasks. Utilize the FPGA's parallelism and reconfigurability to optimize performance for specific applications.

5. Decision Making and Control:

Integrate the FPGA with the overall system for decision making based on image analysis results. This may involve triggering actions, sending alerts, or controlling actuators based on detected objects or events in the scene.

Considerations:

- Resource Utilization: Optimize FPGA resource usage to ensure efficient implementation of image processing algorithms and maximize performance within the device constraints.

- Power Efficiency: Implement power-saving techniques such as clock gating and dynamic voltage scaling to minimize power consumption, especially in battery-powered applications.

- Real-Time Constraints: Design the system to meet real-time processing requirements by carefully scheduling tasks and optimizing algorithm implementations for low latency.

- Scalability and Flexibility: Design the system with scalability in mind to accommodate future algorithm updates or changes in application requirements. Utilize the reconfigurable nature of FPGAs to adapt to evolving needs.

- Integration with Software: Develop software interfaces and drivers to interact with the FPGA-based image processing system, enabling seamless integration with higher-level software applications or systems.

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6. What is the process for return or replacement of LFE2M35E-7FN484C?

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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.

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(3)The PartNo is unused and only in the original unpacked packaging.

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