137
Views
17
CrossRef citations to date
0
Altmetric
Articles

An efficient inexact Full Adder cell design in CNFET technology with high-PSNR for image processing

, ORCID Icon & ORCID Icon
Pages 928-944 | Received 01 Jul 2018, Accepted 18 Nov 2018, Published online: 26 Feb 2019
 

ABSTRACT

The design of inexact circuits at the transistor level remarkably improves figures of merits such as power consumption, delay, energy, and area. Therefore, inexact technique for designing circuits has attracted the attention of researchers worldwide. Designing inexact Full Adder cell as a building block of a variety of arithmetic circuits can affect the entire electronic system’s performance. In this paper, two novel inexact 1-bit Full Adder cells are presented using carbon nanotube field effect transistors (CNFETs). The capacitive threshold logic (CTL) is used to realize the proposed cells. Comprehensive simulations at two levels of abstraction, i.e., application and hardware are carried out to evaluate the efficacy of these circuits. First, the motion detector which is one of the image processing applications is deployed in MATLAB software to measure peak signal-to-noise ratio (PSNR) figure of merit. At hardware level, the HSPICE tool is used to carry out simulations and measure power, delay, power-delay product (PDP), energy-delay product (EDP), power-delay-area product (PDAP) and power-delay-area-PSNR product (PDAPP). Simulation results confirmed the superiority of the proposed Full Adder cells compared to others. For instance, the proposed 6TIFA improves PDAPP metric at least 21% and at most 76% compared to its counterparts at 0.9V power supply.

Disclosure statement

No potential conflict of interest was reported by the authors.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 702.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.