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Name: XC7VX330T-2FFG1761I
Brand: AMD Xilinx
SKU: XC7VX330T-2FFG1761I
Price: 2.40 USD
Availability: InStock
Rating: 5 (2 reviews)

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AMD Xilinx XC7VX330T-2FFG1761I

Part No.:: XC7VX330T-2FFG1761I

Manufacturer:: AMD Xilinx

Package:: 1760-BBGA, FCBGA

Datasheet:: XC7VX330T-2FFG1761I.pdf

Description:: IC FPGA 700 I/O 1761FCBGA

In Stock:: 3115

Quantity:: Add To Cart

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XC7VX330T-2FFG1761I Specifications

Package/Case:
1760-BBGA, FCBGA
Packaging:
Tray
Series:
Virtex®-7 XT
ProductStatus:
Active
NumberofLABs/CLBs:
25500
NumberofLogicElements/Cells:
326400
TotalRAMBits:
27648000
NumberofI/O:
700
NumberofGates:
-
Voltage-Supply:
0.97V ~ 1.03V
MountingType:
Surface Mount
OperatingTemperature:
-40°C ~ 100°C (TJ)

XC7VX330T-2FFG1761I this integrated circuit is available in factory sealed anti static packs. at icwhale.com. Please read product page below detail information. including XC7VX330T-2FFG1761I 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 XC7VX330T-2FFG1761I 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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XC7VX330T-2FFG1761I information

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XC7VX330T-2FFG1761I application case analysis in emerging technology fields

XC7VX330T-2FFG1761I is a high-performance FPGA (Field-Programmable Gate Array) chip designed by Xilinx, offering extensive capabilities for accelerating a wide range of applications. Its advanced architecture and flexible programming make it a suitable choice for demanding tasks in various domains.

Application Scenario:

In the field of image processing and computer vision, XC7VX330T-2FFG1761I can be instrumental in enhancing the efficiency and intelligence of systems. Let's explore how it can be utilized in a specific application: real-time object detection and recognition in autonomous vehicles.

System Architecture:

To implement real-time object detection and recognition using XC7VX330T-2FFG1761I, the system can be divided into several key components:

1. Image Acquisition:

Utilize high-resolution cameras or sensors to capture images of the vehicle's surroundings. These images are then processed by the FPGA for analysis.

2. Image Pre-processing:

Before object detection, apply pre-processing techniques such as noise reduction, image enhancement, and color space conversion to optimize the image data for accurate analysis.

3. Object Detection:

Implement algorithms such as Haar cascades or convolutional neural networks (CNNs) on the FPGA to detect objects within the captured images. The parallel processing capability of XC7VX330T-2FFG1761I accelerates the detection process, enabling real-time performance.

4. Object Recognition:

Once objects are detected, employ pattern recognition algorithms to identify and classify them. This step involves comparing detected features with predefined templates or training data to recognize objects such as vehicles, pedestrians, or traffic signs.

5. Decision Making:

Based on the detected and recognized objects, make real-time decisions to ensure safe navigation and collision avoidance for the autonomous vehicle. This may involve adjusting speed, trajectory, or signaling actions.

Benefits:

By leveraging XC7VX330T-2FFG1761I in real-time object detection and recognition, several benefits can be realized:

- High Performance: The FPGA's parallel processing capability enables rapid analysis of image data, ensuring real-time responsiveness in dynamic environments.

- Flexibility: The programmable nature of FPGAs allows for iterative refinement and optimization of algorithms, adapting to evolving requirements and enhancing system intelligence.

- Low Latency: Direct hardware implementation of algorithms on the FPGA minimizes processing delays, facilitating quick decision-making in safety-critical applications.

- Scalability: The scalable architecture of XC7VX330T-2FFG1761I accommodates future enhancements and expansions, ensuring compatibility with evolving standards and technologies.

- Power Efficiency: Compared to traditional CPU-based solutions, FPGA-based implementations often offer superior energy efficiency, making them suitable for embedded systems with constrained power budgets.

Considerations:

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

- Algorithm Optimization: Fine-tune algorithms to balance accuracy, speed, and resource utilization on the FPGA platform.

- Integration: Ensure seamless integration with other components of the autonomous vehicle system, such as sensors, actuators, and control units.

- Validation: Thoroughly test the system under diverse environmental conditions and scenarios to validate its performance, robustness, and safety.

- Regulatory Compliance: Adhere to relevant regulatory standards and guidelines for autonomous vehicle systems, addressing concerns related to reliability, privacy, and ethical considerations.

XC7VX330T-2FFG1761I FAQ

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6. What is the process for return or replacement of XC7VX330T-2FFG1761I?

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 XC7VX330T-2FFG1761I we delivered, we will accept the replacement or return of the XC7VX330T-2FFG1761I 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 XC7VX330T-2FFG1761I.

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

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(1)Inform us within 90 days

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