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Name: A3PE3000-1FGG324
Brand: Microchip Technology
SKU: A3PE3000-1FGG324
Price: 2.40 USD
Availability: InStock
Rating: 5 (2 reviews)

Any Feature, including a modified Existing Feature, that is not an Existing Feature.

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Microchip Technology A3PE3000-1FGG324

Part No.:: A3PE3000-1FGG324

Manufacturer:: Microchip Technology

Package:: 324-BGA

Datasheet:: A3PE3000-1FGG324.pdf

Description:: IC FPGA 221 I/O 324FBGA

In Stock:: 2151

Quantity:: Add To Cart

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A3PE3000-1FGG324 Specifications

Package/Case:
324-BGA
Packaging:
Tray
Series:
ProASIC3E
ProductStatus:
Active
NumberofLABs/CLBs:
-
NumberofLogicElements/Cells:
-
TotalRAMBits:
516096
NumberofI/O:
221
NumberofGates:
3000000
Voltage-Supply:
1.425V ~ 1.575V
MountingType:
Surface Mount
OperatingTemperature:
0°C ~ 85°C (TJ)

A3PE3000-1FGG324 this integrated circuit is available in factory sealed anti static packs. at icwhale.com. Please read product page below detail information. including A3PE3000-1FGG324 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 A3PE3000-1FGG324 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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A3PE3000-1FGG324 information

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A3PE3000-1FGG324 application case analysis in emerging technology fields

A3PE3000-1FGG324 is a field-programmable gate array (FPGA) chip manufactured by Microsemi Corporation. It offers a versatile platform for implementing custom logic functions and accelerates various applications through parallel processing capabilities.

Application Scenario:

In image processing applications, A3PE3000-1FGG324 can be utilized to enhance efficiency and intelligence. Let's consider the application of real-time object detection and recognition in autonomous vehicles.

Circuit Design:

To implement real-time object detection and recognition using A3PE3000-1FGG324, the following steps can be followed:

1. Sensor Integration:

Integrate sensors such as cameras or LiDARs to capture the surrounding environment. Interface these sensors with the input pins of A3PE3000-1FGG324 to receive image data.

2. Image Preprocessing:

Implement image preprocessing algorithms on A3PE3000-1FGG324 to enhance image quality, remove noise, and extract relevant features. This preprocessing step optimizes subsequent processing stages.

3. Object Detection:

Utilize FPGA logic resources to implement object detection algorithms such as Haar cascades or deep learning-based approaches like convolutional neural networks (CNNs). These algorithms analyze image data to detect objects of interest.

4. Object Recognition:

Implement recognition algorithms on A3PE3000-1FGG324 to classify detected objects. This can involve pattern matching, feature extraction, or neural network-based classification techniques to identify objects like pedestrians, vehicles, or traffic signs.

5. Decision Making:

Based on the detected and recognized objects, make real-time decisions such as vehicle trajectory planning, speed adjustment, or obstacle avoidance strategies. Utilize the processing power of A3PE3000-1FGG324 to ensure quick and accurate decision-making.

Considerations:

When designing the system, several factors should be considered to optimize performance and reliability:

- FPGA Resource Utilization: Efficiently utilize the logic resources and memory blocks of A3PE3000-1FGG324 to accommodate complex algorithms and minimize resource wastage.

- Real-Time Constraints: Ensure that the processing latency meets real-time requirements for applications like autonomous driving, where timely responses are critical for safety.

- Power Efficiency: Optimize the FPGA design to minimize power consumption while maintaining high performance, especially in battery-powered applications like electric vehicles.

- Algorithm Optimization: Fine-tune object detection and recognition algorithms to balance accuracy and computational complexity, considering the limited resources of A3PE3000-1FGG324.

- Integration with System Components: Interface A3PE3000-1FGG324 with other system components such as microcontrollers, sensors, and actuators seamlessly to create a cohesive and intelligent autonomous driving system.

A3PE3000-1FGG324 FAQ

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3. Are the A3PE3000-1FGG324 price and inventory displayed accurate?

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6. What is the process for return or replacement of A3PE3000-1FGG324?

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 A3PE3000-1FGG324 we delivered, we will accept the replacement or return of the A3PE3000-1FGG324 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 A3PE3000-1FGG324.

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

Two processes to return the products:

(1)Inform us within 90 days

(2)Obtain Requesting Return Authorizations