Interpolation for numerical integration

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SUMMARY

The discussion centers on the best interpolation method for the function \(\Gamma(t)\) in the context of numerical integration, specifically within the integral \(\int\Gamma(t) * \tan (\Gamma(t)*t + \varphi)\). Participants suggest that Simpson's rule is a strong candidate for numerical integration methods. The inquiry also explores the potential of using approximations such as Taylor series or sine series to achieve analytical integration of the approximated expression.

PREREQUISITES
  • Understanding of numerical integration techniques, specifically Simpson's rule.
  • Familiarity with interpolation methods for functions defined at discrete points.
  • Knowledge of Taylor series and sine series for function approximation.
  • Basic concepts of integrals and their applications in mathematical analysis.
NEXT STEPS
  • Research the implementation and applications of Simpson's rule in numerical integration.
  • Explore various interpolation methods suitable for discrete functions.
  • Study Taylor series and sine series for approximating functions in integrals.
  • Investigate analytical integration techniques for approximated expressions.
USEFUL FOR

Mathematicians, numerical analysts, and engineers involved in numerical integration and function approximation will benefit from this discussion.

kaniello
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Hallo,
[itex]\Gamma[/itex](t) is a function that i can know only at dicrete points and appears in this integral:
[itex]\int[/itex][itex]\Gamma[/itex](t) * tan ([itex]\Gamma(t)[/itex]*t + [itex]\varphi[/itex])
My question is now, which could be the best interpolation of [itex]\Gamma[/itex](t) that would allopw an exact integration?
Thank you very much in advance
 
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Simpon's rule is definitely a good option. What I was looking for is the following: imagine that in the place of [itex]\Gamma(t)[/itex] you have an approximation, like a Taylor series, or sine series or whatever, that would allow an analytical integration of this approximated expression.
 

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