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A Type of Integrating Formula without Derivative

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Book cover Advances in Neural Networks – ISNN 2009 (ISNN 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5551))

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Abstract

In this paper, A type of integrating formula is constructed, which requires function value at nodes without derivative. In addition, the formula needs less calculation than the Trapezoidal Rule, but the order of convergence is much better. Therefore a more effective .result is obtained.

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References

  1. Zhang, D., Wang, X.: Computational Method Algorithmic Language. Higher Education Press, Beijing (1981)

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  2. Chen, H., Chen, S.: Numerical Computing Methods. Wuhan University Press, Wuhan (2002)

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  3. Liu, C.: A Type of Integrating Formula with Derivative. Journal of Xi’an Technological University 14, 232–237 (1994)

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  4. Liu, C.: A Type of Integrating Formula with Second Derivative. Journal of Xi’an Technological University 18, 247–250 (1998)

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Author information

Authors and Affiliations

  1. College of Computer Science, South-Central University for Nationalities, Wuhan, 430074, People’s Republic of China

    Aifang Long & Di Ning

Authors
  1. Aifang Long
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  2. Di Ning
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Editor information

Editors and Affiliations

  1. Departamento de Control Automático, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, 07360, México D.F., México

    Wen Yu

  2. Deptartment of Electrical and Computer Engineering, Stevens Institute of Technology, NJ 07030, Hoboken, USA

    Haibo He

  3. Dept. of Electrical and Computer Engineering, South Dakota School of Mines & Technology, 501 E. St. Joseph Street, Rapid City, SD 57701, USA

    Nian Zhang

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© 2009 Springer-Verlag Berlin Heidelberg

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Long, A., Ning, D. (2009). A Type of Integrating Formula without Derivative. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5551. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01507-6_23

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  • DOI: https://doi.org/10.1007/978-3-642-01507-6_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01506-9

  • Online ISBN: 978-3-642-01507-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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