http://iet.metastore.ingenta.com
1887

Robust fuzzy SRAM for accurate and ultra-low-power MVL and fuzzy logic applications

Robust fuzzy SRAM for accurate and ultra-low-power MVL and fuzzy logic applications

For access to this article, please select a purchase option:

Buy article PDF
$19.95
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
Electronics Letters — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

A fuzzy static RAM (SRAM) is proposed, which is applicable in fuzzy logic and many multiple-valued logic (MVL) applications. The new structure is basically an extension to the binary SRAM cell. Two cross-coupled voltage mirror circuits are used to be able to hold an arbitrary voltage value. The proposed design forms a robust and reliable structure, which is capable of operating with more than 95% accuracy in spite of imperfect fabrication of carbon nanotube FETs. Another exceptional advantage is its ultra-low-power consumption in MVL environments. It consumes 38.7 and 99% less static power compared with the SRAMs with regular ternary and quaternary components, respectively.

References

    1. 1)
    2. 2)
    3. 3)
    4. 4)
    5. 5)
    6. 6)
      • 6. Kim, Y.B., Kim, Y.-B.: ‘High speed and low power transceiver design with CNFET and CNT bundle interconnect’. 23rd IEEE Int. SOC Conf., Las Vegas, September 2010, pp. 152157.
    7. 7)
      • 7. Patil, N., Deng, J., Wong, H.-S.P., Mitra, S.: ‘Automated design of misaligned-carbon-nanotube-immune circuits’. 44th ACM/IEEE Design Automation Conf., San Diego, June 2007, pp. 958961.
    8. 8)
      • 8. Baturone, I., Barriga, A., Fernandez, J.J., et al: ‘Microelectronic design of fuzzy logic-based systems’ (CRC Press, Boca Raton, FL, USA, 2000).
    9. 9)
      • 9. Stanford University CNFET model website. Available at: https://nano.stanford.edu/model.php.
    10. 10)
    11. 11)
http://iet.metastore.ingenta.com/content/journals/10.1049/el.2016.2932
Loading

Related content

content/journals/10.1049/el.2016.2932
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
Correspondence
This article has following corresponding article(s):
in brief
This is a required field
Please enter a valid email address