Applied and computational complex analysis. Vol. 3: discrete Fourier analysis—Cauchy integrals—construction of conformal maps---univalent functions
Application of a modified FFT to product type integration
ISCM '90 Proceedings of the International Symposium on Computation mathematics
Numerical integration of functions with poles near the interval of integration
Journal of Computational and Applied Mathematics
Journal of Computational and Applied Mathematics - Special issue on numerical analysis in the 20th century vol. 1: approximation theory
Implementing Clenshaw-Curtis quadrature, II computing the cosine transformation
Communications of the ACM
The Accuracy of the Chebyshev Differencing Method for Analytic Functions
SIAM Journal on Numerical Analysis
Pitfalls in fast numerical solvers for fractional differential equations
Journal of Computational and Applied Mathematics
Mechanical quadrature methods and their extrapolation for solving first kind Abel integral equations
Journal of Computational and Applied Mathematics
Quadrature rule for indefinite integral of algebraic-logarithmic singular integrands
Journal of Computational and Applied Mathematics
Is Gauss Quadrature Better than Clenshaw-Curtis?
SIAM Review
Uniform approximation to fractional derivatives of functions of algebraic singularity
Journal of Computational and Applied Mathematics
A Fast Time Stepping Method for Evaluating Fractional Integrals
SIAM Journal on Scientific Computing
An approximation method for high-order fractional derivatives of algebraically singular functions
Computers & Mathematics with Applications
Least-Squares Spectral Method for the solution of a fractional advection-dispersion equation
Journal of Computational Physics
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An automatic quadrature method is presented for approximating fractional derivative D^qf(x) of a given function f(x), which is defined by an indefinite integral involving f(x). The present method interpolates f(x) in terms of the Chebyshev polynomials in the range [0, 1] to approximate the fractional derivative D^qf(x) uniformly for 0@?x@?1, namely the error is bounded independently of x. Some numerical examples demonstrate the performance of the present automatic method.