Approximate multipliers based on a novel unbiased approximate 4-2 compressor

Approximate computing, which relaxes full precision to achieve higher performance or lower power consumption, is widely used in error-resilient applications such as multimedia and machine learning. Multiplication is a fundamental operation for many of these applications. This study presents an unbiased approximate 4-2 compressor that generates positive and negative sign errors in balance. Based on the unbiased 4-2 compressor, two 8 x 8 unbiased approximate multipliers (UBAMs) are designed to meet various accuracy (or power) requirements. Experimental results indicate that one of the proposed designs has a smaller normalized mean error distance (NMED) than previous approximate multipliers, and the other offers a 39% smaller power-delay product (PDP) and almost 46% smaller energy-delay product (EDP). The proposed multipliers outperform other approximate designs in image filtering applications by achieving higher quality outputs with lower power consumption.