Function approximation, a central theme in numerical analysis and applied mathematics, seeks to represent complex functions through simpler or more computationally tractable forms. In this context, ...

Mathematics of Computation, Vol. 84, No. 294 (JULY 2015), pp. 1835-1860 (26 pages) The Padé approximation has a long and rich history of theory and application and is known to produce excellent local ...

Abstract: In this paper we study the accuracy and convergence of state-space approximations of Gaussian processes (GPs) with squared exponential (SE) covariance functions. This kind of approximations ...

This is a preview. Log in through your library . Abstract Gaussian process models have been widely used in spatial statistics but face tremendous computational challenges for very large data sets. The ...

The FD= and FDHESSIAN= options specify the use of finite difference approximations of the derivatives. The FD= option specifies that all derivatives are approximated using function evaluations, and ...

Matrix functions, such as the exponential, square root and cosine, play an indispensable role in various fields including quantum mechanics, control theory and numerical solution of differential ...

Implementing exact approximations to functions. For example, by representing approximate real numbers by an interval, complex numbers by a box, p-adics by a ball, etc. From here we should have a solid ...

The circumference of a sphere is measured to be 24 cm, with a possible error of 0.25 cm. Use the differential \(dV\) to estimate the maximum error in the calculated ...

Abstract: A method to approximate functions of two variables is presented; it is suitable for hardware implementations based on digital or mixed signal architectures. Such a method is based on the ...