Scholarlink

<p>Approximate computing has appeared as a good solution to limited energy, error-tolerant applications like image processing with a trade-off between efficiency and accuracy. This paper introduces three new approximate full adder (AFA) circuits—prop_AFA1, prop_AFA2, and prop_AFA3 based on carbon nanotube field-effect transistor (CNTFET) technology and the gate diffusion input (GDI) method, incorporating dynamic-threshold (DT) control to enhance stability and performance. The designs realise impressive reductions in transistor count (6–8 per cell), leading to considerable improvements in power, delay, power-delay product (PDP), and power-delay-area product (PDAP) over the currently known AFAs. Prop_AFA1 gives the overall best performance with 22 nW power, 2.64 aJ PDP, and 126.7 PDAP units in 8-bit RCAs with 96.44% PDAP improvement over GDI_AFA. Prop_AFA3 has 68.5% reduced power and 92.8% reduced PDAP compared to NxFA. The NMED values are 0.243, 0.167, and 0.272 for prop_AFA1, prop_AFA2, and prop_AFA3, respectively, of which prop_AFA2 gives maximum output accuracy. Upon incorporation into 8-bit and 16-bit RCAs and tested in image smoothness filters, the proposed architectures demonstrate higher PDP, with prop_AFA1 being superior to prop_AFA2 by 50% and prop_AFA2 performing better than prop_AFA3 by 78.6%. These findings identify the proposed AFAs as viable contenders for next-generation low-power, high-efficiency VLSI systems for approximate arithmetic and image processing computations.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

An energy efficient approximate CNTFET based full adders with GDI technique for image processing applications

  • 期刊论文

  • 发表日期：

    2025年12月2日

查看全文
  • H. K. Raghu Vamsi Kudulla,
  • Sankranti Srinivasa Rao

摘要

Approximate computing has appeared as a good solution to limited energy, error-tolerant applications like image processing with a trade-off between efficiency and accuracy. This paper introduces three new approximate full adder (AFA) circuits—prop_AFA1, prop_AFA2, and prop_AFA3 based on carbon nanotube field-effect transistor (CNTFET) technology and the gate diffusion input (GDI) method, incorporating dynamic-threshold (DT) control to enhance stability and performance. The designs realise impressive reductions in transistor count (6–8 per cell), leading to considerable improvements in power, delay, power-delay product (PDP), and power-delay-area product (PDAP) over the currently known AFAs. Prop_AFA1 gives the overall best performance with 22 nW power, 2.64 aJ PDP, and 126.7 PDAP units in 8-bit RCAs with 96.44% PDAP improvement over GDI_AFA. Prop_AFA3 has 68.5% reduced power and 92.8% reduced PDAP compared to NxFA. The NMED values are 0.243, 0.167, and 0.272 for prop_AFA1, prop_AFA2, and prop_AFA3, respectively, of which prop_AFA2 gives maximum output accuracy. Upon incorporation into 8-bit and 16-bit RCAs and tested in image smoothness filters, the proposed architectures demonstrate higher PDP, with prop_AFA1 being superior to prop_AFA2 by 50% and prop_AFA2 performing better than prop_AFA3 by 78.6%. These findings identify the proposed AFAs as viable contenders for next-generation low-power, high-efficiency VLSI systems for approximate arithmetic and image processing computations.