Memristor-Based Approximate Adders for Efficient In-Memory Computing in Image Processing

This paper presents two novel memristor-based approximate adder designs using the V/R-R logic principle to enhance in-memory computing (IMC) efficiency while balancing accuracy. These adders leverage approximate computation to improve the performance tolerant of minor precision losses in applications such as image processing. Experimental and simulation results demonstrate significant improvements in computational speed and area efficiency over conventional designs. Integrated into a ripple carry adder (RCA), the proposed designs maintain acceptable image quality for image addition, with peak signal-to-noise ratio (PSNR) exceeding 30 dB in most cases.

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Published
2025-03-09
DOI
https://doi.org/10.1109/edtm61175.2025.11040549
Primary Topic
Advanced Memory and Neural Computing
Type
article
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article

Memristor-Based Approximate Adders for Efficient In-Memory Computing in Image Processing

Xingsheng Wang, Cheng Fang, Xiangshui Miao, Mengjie Li et al.
Advanced Memory and Neural Computing
article

Memristor-Based Approximate Adders for Efficient In-Memory Computing in Image Processing

Xingsheng Wang, Cheng Fang, Xiangshui Miao, Mengjie Li, Fan Yang, Zhouchao Gan
article en

Abstract

This paper presents two novel memristor-based approximate adder designs using the V/R-R logic principle to enhance in-memory computing (IMC) efficiency while balancing accuracy. These adders leverage approximate computation to improve the performance tolerant of minor precision losses in applications such as image processing. Experimental and simulation results demonstrate significant improvements in computational speed and area efficiency over conventional designs. Integrated into a ripple carry adder (RCA), the proposed designs maintain acceptable image quality for image addition, with peak signal-to-noise ratio (PSNR) exceeding 30 dB in most cases.

Wuhan National Laboratory for Optoelectronics (CN), Huazhong University of Science and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 87%
Advanced Memory and Neural Computing
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