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 × 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.

近似计算放宽了全精度以实现更高的性能或更低的功耗，广泛用于容错应用，例如多媒体和机器学习。乘法是许多这些应用程序的基本运算。本研究提出了一种无偏的近似 4-2 压缩器，可在平衡中产生正负符号误差。基于无偏 4-2 压缩器，设计了两个 8 × 8 无偏近似乘法器 (UBAM)，以满足各种精度（或功率）要求。实验结果表明，所提出的设计之一具有比以前的近似乘法器更小的归一化平均误差距离 (NMED)，而另一个设计的功率延迟积 (PDP) 小 39%，能量延迟积 (EDP) 小了近 46%。 ）。