Abstract
Field Programmable Gate Arrays (FPGAs) have emerged as an ideal solution for high-performance embedded systems, offering a balance between flexibility, parallel processing, and low latency. This paper explores FPGA design techniques for optimizing embedded systems across various applications such as real-time processing, machine learning, and embedded control systems. We analyze the architecture of FPGAs, focusing on key design aspects like resource allocation, clock management, and hardware/software co-design. Practical case studies on FPGA applications demonstrate their ability to meet the demanding performance requirements of embedded systems while maintaining efficiency and scalability.

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