Search

• Using the carbon nanotube field-effect transistors technology to design approximate arithmetic circuits. • The gate diffusion input and dynamic threshold techniques are integrated to attain efficient circuits. • The presented approximate full adders show reliable performance during image processing. • The approximate full adders applied in bioimage processing. • Fat and water can be detected in bioimages by the presented approximate cells. Two new approximate full adders (FAs) are proposed by the multiplexers (MUXs) and OR gates with the gate diffusion input (GDI) technique. The cells are named GDI-based MUX approximate FAs (GMAFAs), GMAFA1, and GMAFA2. The threshold voltage drop of the GDI-based circuits is solved by carbon nanotube field-effect transistors (CNTFETs) technology and the dynamic threshold (DT) technique. The FAs have accurate C out , approximate Sum, and a low number of transistors. They are low-power, high-speed, and energy-efficient for ripple-carry adders (RCAs). The GMAFA1 and GMAFA2 have a total area of 0.068 µm2 and 0.119 µm2, respectively, which demonstrate 27.8% and 54.55% improvement in power-delay-area-product (PDAP) in comparison with the best references. The results of error distance (ED), normalized mean error distance (NMED), power signal-to-noise ratio (PSNR), and energy-saving confirm the accuracy of the presented cells for image processing applications. [Display omitted] [ABSTRACT FROM AUTHOR]

• Using the gate diffusion input technique in a new approximate full adder. • The full adder is implemented by carbon nanotube field-effect transistors. • The dynamic threshold technique improves the full adder swing. • A new approximate subtractor implemented by the full adder. • The approximate full adder and subtractor detect brain stroke. Approximate circuits are used in fault-tolerance applications, where carbon nanotube field-effect transistor (CNTFET) technology assists to achieve high performance. In this study, a new 8-transistor approximate full adder (FA) is designed and implemented using CNTFETs based on the gate diffusion input (GDI) technique. The FA is implemented in a ripple carry adder (RCA) and a 4-bit inexact subtractor for bioimages difference detection and finally stroke recognition. The non-full-swing outputs of the presented GDI cells are obviated by the dynamic threshold (DT) technique. The presented FA consumes a power of 2.0446 µW, while its power-delay-product (PDP) is 6.4536 fJ. Also, the superior results of peak signal-to-noise ratio (PSNR), power consumption, and PDP of the proposed subtractor are 30.866 dB, 9.642 µW, and 314.907 fJ, respectively. The FA has an area of 0.161 µm2 while the 4-bit subtractor occupies 2.18 µm2. The presented circuits show efficient performance for bioelectronics integrated circuits (ICs). [Display omitted] [ABSTRACT FROM AUTHOR]