文件名称:Gaussian
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The numerical integration methods described so far are based on a rather simple choice of evaluation points
for the function f(x). They are particularly suited for regularly tabulated data, such as one might measure in a
laboratory, or obtain from computer software designed to produce tables. If one has the freedom to choose
the points at which to evaluate f(x), a careful choice can lead to much more accuracy in evaluating the
integral in question. We shall see that this method, called Gaussian or Gauss-Legendre integration, has one
significant further advantage in many situations. In the evaluation of an integral on the interval to , it is
for the function f(x). They are particularly suited for regularly tabulated data, such as one might measure in a
laboratory, or obtain from computer software designed to produce tables. If one has the freedom to choose
the points at which to evaluate f(x), a careful choice can lead to much more accuracy in evaluating the
integral in question. We shall see that this method, called Gaussian or Gauss-Legendre integration, has one
significant further advantage in many situations. In the evaluation of an integral on the interval to , it is
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Gaussian Quadrature.pdf