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Projection methods based on grids for weakly singular integral equations

机译:弱奇异积分方程的网格投影方法

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For the solution of a weakly singular Fredholm integral equation of the 2nd kind defined on a Banach space, for instance L~1([a,b]), the classical projection methods with the discretization of the approximating operator on a finite dimensional subspace usually use a basis of this subspace built with grids on [a, b]. This may require a large dimension of the subspace. One way to overcome this problem is to include more information in the approximating operator or to compose one classical method with one step of iterative refinement This is the case of Kulkarni method or iterated Kantorovich method. Here we compare these methods in terms of accuracy and arithmetic workload. A theorem stating comparable error bounds for these methods, under very weak assumptions on the kernel, the solution and the space where the problem is set, is given.
机译:为了解决在Banach空间上定义的第二类弱奇异Fredholm积分方程,例如L〜1([a,b]),通常在有限维子空间上采用近似算子离散化的经典投影方法使用在[a,b]上以网格构建的子空间的基础。这可能需要较大尺寸的子空间。解决此问题的一种方法是在逼近算子中包含更多信息,或者用一个迭代精炼步骤组合一个经典方法,这就是Kulkarni方法或迭代Kantorovich方法的情况。在这里,我们从准确性和算术工作量方面比较这些方法。给出了一个定理,说明在内核,解和问题所在的空间非常弱的假设下,这些方法的可比误差范围。

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