2010
DOI: 10.1016/j.cam.2009.11.031
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Product integration methods based on discrete spline quasi-interpolants and application to weakly singular integral equations

Abstract: International audienceQuadrature formulae are established for product integration rules based on discrete spline quasi-interpolants on a bounded interval. The integrand considered may have algebraic or logarithmic singularities. These formulae are then applied to the numerical solution of integral equations with weakly singular kernels

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Cited by 30 publications
(15 citation statements)
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“…The use of splines in the numerical solution of integral equations has been investigated by many authors [2], [4], [10], [12], [13], [15], [16], [21], [26], [29]. While most of these work employs continuous splines, there are only very few papers that involve discrete splines, as such our work naturally complements the literature and in particular is applicable to more general integral equations.…”
Section: Introductionmentioning
confidence: 63%
“…The use of splines in the numerical solution of integral equations has been investigated by many authors [2], [4], [10], [12], [13], [15], [16], [21], [26], [29]. While most of these work employs continuous splines, there are only very few papers that involve discrete splines, as such our work naturally complements the literature and in particular is applicable to more general integral equations.…”
Section: Introductionmentioning
confidence: 63%
“…The use of splines in the numerical solution of integral equations has been investigated by many authors [7][8][9][10][22][23][24][25][26][27][28][29]. While most of these studies employ continuous splines, there are only very few papers that involve discrete splines, as such our work naturally complements the literature and in particular is applicable to more general integral equations.…”
Section: Introductionmentioning
confidence: 69%
“…Table 4 shows the absolute errors which computed by using proposed method. Also, Comparison is made with the result presented in [10,18]. There the maximum error is de ned as MaxError = max|ϕ(x) − ϕ N (x)|, to calculate the errors in Table 4.…”
Section: Examplementioning
confidence: 99%