Advertisement

Iyengar Fuzzy Inequalities

  • George A. AnastassiouEmail author
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 886)

Abstract

Here we present fuzzy Iyengar type inequalities for continuous fuzzy number valued functions. These functions fulfill some type of Lipschitz conditions. See also [3].

References

  1. 1.
    G.A. Anastassiou, Rate of convergence of fuzzy neural network operators, univariate case. J. Fuzzy Math. 10(3), 755–780 (2002)MathSciNetzbMATHGoogle Scholar
  2. 2.
    G.A. Anastassiou, Fuzzy Mathematics: Approximation Theory (Springer, Heidelberg, 2010)CrossRefGoogle Scholar
  3. 3.
    G.A. Anastassiou, Fuzzy Iyengar Type Inequalities, Computational and Applied Mathematics (2019)Google Scholar
  4. 4.
    G.A. Anastassiou, S. Gal, On a fuzzy trigonometric approximation theorem of Weierstrass-type. J. Fuzzy Math. 9(3), 701–708 (2001), Los AngelesGoogle Scholar
  5. 5.
    S. Gal, Approximation theory in fuzzy setting, in Handbook of Analytic - Computational Methods in Applied Mathematics, ed. by G. Anastassiou (Chapman & Hall/CRC, Boca Raton, 2000), pp. 617–666Google Scholar
  6. 6.
    R. Goetschel Jr., W. Voxman, Elementary fuzzy calculus. Fuzzy Sets Syst. 18, 31–43 (1986)MathSciNetCrossRefGoogle Scholar
  7. 7.
    K.S.K. Iyengar, Note on an inequality. Math. Student 6, 75–76 (1938)zbMATHGoogle Scholar
  8. 8.
    Z. Liu, Note on Iyengar’s inequality. Univ. Beograd, Publ. Elektrotehn, FAK, Ser. Mat. 16, 29–35 (2005)Google Scholar
  9. 9.
    C. Wu, M. Ming, On embedding problem of fuzzy number space: part 1. Fuzzy Sets Syst. 44, 33–38 (1991)Google Scholar
  10. 10.
    C. Wu, Z. Gong, On Henstock integral of fuzzy number valued functions (I). Fuzzy Sets Syst. 120(3), 523–532 (2001)MathSciNetCrossRefGoogle Scholar

Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Mathematical SciencesUniversity of MemphisMemphisUSA

Personalised recommendations