提出了一种基于静态分段补偿方法的近似乘法器。通过基于静态分段方法的Booth编码方法生成部分积阵列, 并对生成的部分积阵列进行误差补偿优化以及近似压缩, 以实现硬件性能和精度的折中。仿真结果显示, 相比于综合工具生成的全精度乘法器, 本设计在保持了较高精度水平的前提下, 面积和功耗优化的比例达到了36.96%和35.95%。在图片边缘检测应用中, 设计的峰值信噪比和结构相似性指标分别为26.10和98%, 可见本设计在降低硬件资源消耗的同时, 应用效果接近全精度乘法器。

An approximate multiplier based on static segment method was proposed. The partial product array was generated by modified Booth encoding method based on static segment method. After Booth encoding, the generated partial product array was optimized with error compensation and compressed by approximate compressing tree to achieve a compromise between hardware performance and accuracy. The simulation results show that, compared with the full-precision multiplier generated by the EDA tool, the proposed design reduces the area and power consumption by 36.96% and 35.95% respectively while maintaining high precision. In the application of image edge detection, the peak signal-to-noise ratio and structural similarity index of the proposed design are 26.10 and 98% respectively, indicating that the application result is close to that of full-precision multiplier while reducing hardware resource consumption.