Finite Impulse Response (FIR) filters are integral to modern digital signal processing applications requiring high throughput and low latency. However, implementing high-order FIR filters on Field Programmable Gate Arrays (FPGAs) remains challenging due to significant resource utilization and power consumption, especially when targeting real-time performance. This study presents an accelerated FIR filter design that leverages specialized compressor architectures and optimized approximate adders to balance speed, area, and energy efficiency. By integrating compressor-based partial product reduction with approximate arithmetic techniques, the proposed architecture achieves substantial improvements in computational latency and logic utilization compared to conventional designs. Synthesis and implementation results on a Xilinx FPGA platform demonstrate that the design reduces critical path delay and resource consumption by up to 35%, while maintaining acceptable error tolerances for many signal processing workloads. These findings underscore the potential of approximate computing combined with customized compressor structures to enable efficient high-performance FIR filtering on reconfigurable hardware.

FIR filter design, FPGA acceleration, Compressor architectures

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