Benchmarking Finite Order Filter Algorithms On Low Power Embedded Processors : Computing Efficiency

Efficient signal processing in embedded systems hinges on selecting the right microcontroller for your Finite Impulse Response (FIR) filter needs, yet engineers often struggle without clear guidelines for making this crucial decision. Our research tackles this practical challenge by systematically studying how different filter complexities affect microcontroller performance across key areas like processing speed, memory usage, CPU load, and power consumption. We discovered that complex, high-order filters need powerful microcontrollers with robust processing capabilities and ample memory, while simpler, low-order filters work perfectly well on energy-efficient, low- power chips that prioritize battery life over raw performance. The results indicate that a 51st-order filter utilizes nearly 76% of the available 2 KB SRAM, beyond which the system exhibits frequent instability stemming from insufficient memory allocation for reliable runtime operations. These findings give embedded system designers a straightforward framework for choosing microcontrollers that strike the right balance between getting the job done and conserving power. By understanding these relationships, engineers can make smarter hardware decisions that deliver effective signal processing while keeping systems efficient and sustainable, ultimately leading to better-performing embedded devices that don’t waste precious resources.