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A formula in which the nodes (cf. [[Node|Node]]) nearest to the interpolation point <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/g/g043/g043440/g0434401.png" /> are used as interpolation nodes. If <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/g/g043/g043440/g0434402.png" />, the formula
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<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/g/g043/g043440/g0434403.png" /></td> <td valign="top" style="width:5%;text-align:right;">(1)</td></tr></table>
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{{TEX|done}}
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/g/g043/g043440/g0434404.png" /></td> </tr></table>
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A formula in which the nodes (cf. [[Node|Node]]) nearest to the interpolation point  $  x $
 +
are used as interpolation nodes. If  $  x = x _ {0} + th $,
 +
the formula
  
written with respect to the nodes <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/g/g043/g043440/g0434405.png" />, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/g/g043/g043440/g0434406.png" />, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/g/g043/g043440/g0434407.png" /> is called the Gauss forward interpolation formula, while the formula
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$$ \tag{1 }
 +
G _ {2n + 1 }
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( x _ {0} + th)  = \
 +
f _ {0} + f _ {1/2} ^ { 1 } t +
 +
f _ {0} ^ { 2 }
 +
\frac{t ( t - 1) }{2!}
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+ \dots +
 +
$$
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/g/g043/g043440/g0434408.png" /></td> <td valign="top" style="width:5%;text-align:right;">(2)</td></tr></table>
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$$
 +
+
 +
f _ {0} ^ { 2n }
 +
\frac{t ( t  ^ {2} - 1) \dots [ t
 +
^ {2} - ( n - 1)  ^ {2} ] ( t - n) }{( 2n)! }
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,
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$$
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/g/g043/g043440/g0434409.png" /></td> </tr></table>
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written with respect to the nodes  $  x _ {0} , x _ {0} + h $,
 +
$  h _ {0} - h \dots x _ {0} + nh $,
 +
$  x _ {0} - nh $
 +
is called the Gauss forward interpolation formula, while the formula
  
written with respect to the nodes <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/g/g043/g043440/g04344010.png" />, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/g/g043/g043440/g04344011.png" />, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/g/g043/g043440/g04344012.png" /> is called the Gauss backward interpolation formula, [[#References|[1]]], [[#References|[2]]]. Formulas (1) and (2) employ finite differences, defined as follows:
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$$ \tag{2 }
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G _ {2n + 1 }  ( x _ {0} + th)  = \
 +
f _ {0} + f _ {-} 1/2 ^ { 1 } t + f _ {0} ^ { 2 }
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/g/g043/g043440/g04344013.png" /></td> </tr></table>
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\frac{t ( t + 1) }{2! }
 +
+ \dots +
 +
$$
 +
 
 +
$$
 +
+
 +
f _ {0} ^ { 2n }
 +
\frac{t ( t  ^ {2} - 1) \dots [ t
 +
^ {2} - ( n - 1)  ^ {2} ] ( t + n) }{( 2n)! }
 +
,
 +
$$
 +
 
 +
written with respect to the nodes  $  x _ {0} , x - h $,
 +
$  x _ {0} + h \dots x _ {0} - nh $,
 +
$  x _ {0} + nh $
 +
is called the Gauss backward interpolation formula, [[#References|[1]]], [[#References|[2]]]. Formulas (1) and (2) employ finite differences, defined as follows:
 +
 
 +
$$
 +
f _ {i + 1/2 }  ^ { 1 }  = f _ {i + 1 }  - f _ {i} ,\ \
 +
f _ {i} ^ { m }  = \
 +
f _ {i + 1/2 }  ^ { m - 1 } -
 +
f _ {i - 1/2 }  ^ { m - 1 } .
 +
$$
  
 
The advantage of Gauss' interpolation formulas consists in the fact that this selection of interpolation nodes ensures the best approximation of the residual term of all possible choices, while the ordering of the nodes by their distances from the interpolation point reduces the numerical error in the interpolation.
 
The advantage of Gauss' interpolation formulas consists in the fact that this selection of interpolation nodes ensures the best approximation of the residual term of all possible choices, while the ordering of the nodes by their distances from the interpolation point reduces the numerical error in the interpolation.
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====References====
 
====References====
 
<table><TR><TD valign="top">[1]</TD> <TD valign="top">  I.S. Berezin,  N.P. Zhidkov,  "Computing methods" , '''1''' , Pergamon  (1973)  (Translated from Russian)</TD></TR><TR><TD valign="top">[2]</TD> <TD valign="top">  N.S. Bakhvalov,  "Numerical methods: analysis, algebra, ordinary differential equations" , MIR  (1977)  (Translated from Russian)</TD></TR></table>
 
<table><TR><TD valign="top">[1]</TD> <TD valign="top">  I.S. Berezin,  N.P. Zhidkov,  "Computing methods" , '''1''' , Pergamon  (1973)  (Translated from Russian)</TD></TR><TR><TD valign="top">[2]</TD> <TD valign="top">  N.S. Bakhvalov,  "Numerical methods: analysis, algebra, ordinary differential equations" , MIR  (1977)  (Translated from Russian)</TD></TR></table>
 
 
  
 
====Comments====
 
====Comments====
 
  
 
====References====
 
====References====
 
<table><TR><TD valign="top">[a1]</TD> <TD valign="top">  P.J. Davis,  "Interpolation and approximation" , Dover, reprint  (1975)  pp. 108–126</TD></TR><TR><TD valign="top">[a2]</TD> <TD valign="top">  F.B. Hildebrand,  "Introduction to numerical analysis" , McGraw-Hill  (1974)</TD></TR><TR><TD valign="top">[a3]</TD> <TD valign="top">  J.F. Steffensen,  "Interpolation" , Chelsea, reprint  (1950)</TD></TR></table>
 
<table><TR><TD valign="top">[a1]</TD> <TD valign="top">  P.J. Davis,  "Interpolation and approximation" , Dover, reprint  (1975)  pp. 108–126</TD></TR><TR><TD valign="top">[a2]</TD> <TD valign="top">  F.B. Hildebrand,  "Introduction to numerical analysis" , McGraw-Hill  (1974)</TD></TR><TR><TD valign="top">[a3]</TD> <TD valign="top">  J.F. Steffensen,  "Interpolation" , Chelsea, reprint  (1950)</TD></TR></table>

Revision as of 19:41, 5 June 2020


A formula in which the nodes (cf. Node) nearest to the interpolation point $ x $ are used as interpolation nodes. If $ x = x _ {0} + th $, the formula

$$ \tag{1 } G _ {2n + 1 } ( x _ {0} + th) = \ f _ {0} + f _ {1/2} ^ { 1 } t + f _ {0} ^ { 2 } \frac{t ( t - 1) }{2!} + \dots + $$

$$ + f _ {0} ^ { 2n } \frac{t ( t ^ {2} - 1) \dots [ t ^ {2} - ( n - 1) ^ {2} ] ( t - n) }{( 2n)! } , $$

written with respect to the nodes $ x _ {0} , x _ {0} + h $, $ h _ {0} - h \dots x _ {0} + nh $, $ x _ {0} - nh $ is called the Gauss forward interpolation formula, while the formula

$$ \tag{2 } G _ {2n + 1 } ( x _ {0} + th) = \ f _ {0} + f _ {-} 1/2 ^ { 1 } t + f _ {0} ^ { 2 } \frac{t ( t + 1) }{2! } + \dots + $$

$$ + f _ {0} ^ { 2n } \frac{t ( t ^ {2} - 1) \dots [ t ^ {2} - ( n - 1) ^ {2} ] ( t + n) }{( 2n)! } , $$

written with respect to the nodes $ x _ {0} , x - h $, $ x _ {0} + h \dots x _ {0} - nh $, $ x _ {0} + nh $ is called the Gauss backward interpolation formula, [1], [2]. Formulas (1) and (2) employ finite differences, defined as follows:

$$ f _ {i + 1/2 } ^ { 1 } = f _ {i + 1 } - f _ {i} ,\ \ f _ {i} ^ { m } = \ f _ {i + 1/2 } ^ { m - 1 } - f _ {i - 1/2 } ^ { m - 1 } . $$

The advantage of Gauss' interpolation formulas consists in the fact that this selection of interpolation nodes ensures the best approximation of the residual term of all possible choices, while the ordering of the nodes by their distances from the interpolation point reduces the numerical error in the interpolation.

References

[1] I.S. Berezin, N.P. Zhidkov, "Computing methods" , 1 , Pergamon (1973) (Translated from Russian)
[2] N.S. Bakhvalov, "Numerical methods: analysis, algebra, ordinary differential equations" , MIR (1977) (Translated from Russian)

Comments

References

[a1] P.J. Davis, "Interpolation and approximation" , Dover, reprint (1975) pp. 108–126
[a2] F.B. Hildebrand, "Introduction to numerical analysis" , McGraw-Hill (1974)
[a3] J.F. Steffensen, "Interpolation" , Chelsea, reprint (1950)
How to Cite This Entry:
Gauss interpolation formula. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Gauss_interpolation_formula&oldid=13324
This article was adapted from an original article by M.K. Samarin (originator), which appeared in Encyclopedia of Mathematics - ISBN 1402006098. See original article