The worst case complexity of the fredholm equation with periodic free term and noisy information

This paper deals with the complexity of the Fredholm equation La = f of the second kind with f is an element of H'(Gamma) in a periodic setting. The problem elements are free term f and belong to the unit ball of H'(Gamma). Available information about the problem element f is assumed to be corrupted by bounded noise. First, we give the order of the n-the optimal radius in the worst case setting. Then, we show that the Galerkin method using 2n + 1 inner products off has minimal error. Finally, we give the estimate of E-complexity of the Fredholm integral equation of the second kind and the Galerkin method in the worst case setting.

[1]  Misako Yokoyama Computing topological degree using noisy information , 1990, J. Complex..

[2]  K. Qureshi,et al.  Some problems of approximation theory , 1981 .

[3]  Misako Yokoyama Computing the Topological Degree with Noisy Information , 1997, J. Complex..

[4]  Sergei V. Pereverzyev,et al.  The Minimal Radius of Galerkin Information for the Fredholm Problem of the First Kind , 1996, J. Complex..

[5]  Stefan Heinrich,et al.  Complexity of local solution of integral equations , 1994 .

[6]  Leszek Plaskota,et al.  Worst Case Complexity of Problems with Random Information Noise , 1996, J. Complex..

[7]  Tianzi Jiang,et al.  The average case complexity of the Fredholm equation of second kind with free term in Hr (Γ) , 1996 .

[8]  Karin Frank Complexity of Local Solution of Multivariate Integral Equations , 1995, J. Complex..

[9]  J. F. Traub,et al.  Information-Based complexity: New questions for mathematicians , 1991 .

[10]  Tianzi Jiang,et al.  The worst case complexity of the Fredholm equation of the second kind with non-periodic free term and noise information , 1998 .

[11]  Stefan Heinrich Probabilistic Analysis of Numerical Methods for Integral Equations , 1991 .

[12]  Arthur G. Werschulz,et al.  Computational complexity of differential and integral equations - an information-based approach , 1991, Oxford mathematical monographs.

[13]  Leszek Plaskota How to Benefit from Noise , 1996, J. Complex..

[14]  H. Woxniakowski Information-Based Complexity , 1988 .

[15]  S. V. Pereverzev,et al.  On the optimization of projection-iterative methods for the approximate solution of ill-posed problems , 1996 .

[16]  A. Werschulz What is the Complexity of the Fredholm Problem of the Second Kind , 1984 .

[17]  Arthur G. Werschulz,et al.  The Complexity of Definite Elliptic Problems with Noisy Data , 1996, J. Complex..

[18]  Stefan Heinrich,et al.  Probabilistic complexity analysis for linear problems in bounded domains , 1990, J. Complex..

[19]  Arthur G. Werschulz Complexity of differential and integral equations , 1985, J. Complex..

[20]  R. Kress Linear Integral Equations , 1989 .

[21]  Karin Frank,et al.  Information Complexity of Multivariate Fredholm Integral Equations in Sobolev Classes , 1996, J. Complex..