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Name: LFE3-35EA-6FTN256I
Brand: Lattice Semiconductor Corporation
SKU: LFE3-35EA-6FTN256I
Price: 2.40 USD
Availability: InStock
Rating: 5 (2 reviews)

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Lattice Semiconductor Corporation LFE3-35EA-6FTN256I

Part No.:: LFE3-35EA-6FTN256I

Manufacturer:: Lattice Semiconductor Corporation

Package:: 256-BGA

Datasheet:: LFE3-35EA-6FTN256I.pdf

Description:: IC FPGA 133 I/O 256FTBGA

In Stock:: 2260

Quantity:: Add To Cart

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LFE3-35EA-6FTN256I Specifications

Package/Case:
256-BGA
Packaging:
Tray
Series:
ECP3
ProductStatus:
Active
NumberofLABs/CLBs:
4125
NumberofLogicElements/Cells:
33000
TotalRAMBits:
1358848
NumberofI/O:
133
NumberofGates:
-
Voltage-Supply:
1.14V ~ 1.26V
MountingType:
Surface Mount
OperatingTemperature:
-40°C ~ 100°C (TJ)

LFE3-35EA-6FTN256I this integrated circuit is available in factory sealed anti static packs. at icwhale.com. Please read product page below detail information. including LFE3-35EA-6FTN256I 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 LFE3-35EA-6FTN256I 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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LFE3-35EA-6FTN256I information

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LFE3-35EA-6FTN256I application case analysis in emerging technology fields

LFE3-35EA-6FTN256I is a field-programmable gate array (FPGA) device manufactured by Lattice Semiconductor. It offers high-performance logic, memory, and DSP capabilities, making it suitable for a wide range of applications requiring real-time processing and flexibility.

Application Scenario:

In the field of image processing, LFE3-35EA-6FTN256I can significantly enhance efficiency and intelligence in various tasks, such as object recognition in surveillance systems.

System Architecture:

To implement an object recognition system using LFE3-35EA-6FTN256I, the following architectural components can be utilized:

1. Image Sensor Interface:

Connect an image sensor module, such as a CMOS camera, to the input pins of LFE3-35EA-6FTN256I. Implement interface logic to process the raw image data from the sensor.

2. Image Preprocessing:

Utilize the FPGA's DSP resources to perform preprocessing tasks like noise reduction, edge detection, and image enhancement. These operations help improve the quality of input images for subsequent processing stages.

3. Feature Extraction:

Implement algorithms for feature extraction to identify key characteristics of objects in the scene. Utilize the FPGA's logic resources to efficiently extract relevant features such as shapes, textures, and colors.

4. Object Classification:

Utilize machine learning algorithms or predefined classifiers to analyze the extracted features and classify objects within the image. Implement these algorithms using the FPGA's embedded memory and computational resources.

5. Output Interface:

Connect output devices, such as displays or actuators, to the FPGA's output pins. Display the results of object recognition, such as bounding boxes around detected objects, or trigger actions based on classification results.

Key Advantages:

- Real-Time Processing: The parallel processing architecture of LFE3-35EA-6FTN256I enables real-time image analysis, crucial for applications requiring rapid response times.

- Flexibility: FPGA-based solutions offer flexibility in algorithm implementation, allowing for customization and optimization of image processing pipelines according to specific application requirements.

- Low Latency: With optimized hardware implementations, LFE3-35EA-6FTN256I can achieve low latency in image processing tasks, enhancing overall system performance.

- Power Efficiency: FPGA devices like LFE3-35EA-6FTN256I offer power-efficient operation compared to traditional CPU-based solutions, making them suitable for battery-powered or energy-constrained applications.

Considerations:

- Resource Utilization: Efficient utilization of FPGA resources is essential to maximize performance and minimize cost. Careful design and optimization of algorithms are necessary to achieve the desired functionality within the available hardware constraints.

- Algorithm Complexity: Complex image processing algorithms may require significant FPGA resources and may necessitate trade-offs between performance, resource utilization, and power consumption.

- Integration Challenges: Integrating FPGA-based solutions into existing systems may require compatibility with other hardware components and software interfaces. Proper interfacing and communication protocols should be considered during system design.

- Verification and Testing: Thorough testing and validation are crucial to ensure the accuracy and reliability of the object recognition system implemented using LFE3-35EA-6FTN256I. Comprehensive testing methodologies should be employed to verify the system's performance under various operating conditions.

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6. What is the process for return or replacement of LFE3-35EA-6FTN256I?

All goods will implement Pre-Shipment Inspection (PSI), selected at random from all batches of your order to do a systematic inspection before arranging the shipment. If there is something wrong with the LFE3-35EA-6FTN256I we delivered, we will accept the replacement or return of the LFE3-35EA-6FTN256I only when all of the below conditions are fulfilled:

(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 LFE3-35EA-6FTN256I.

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

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