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 ...
Abstract: This paper describes a simple procedure for synthesizing an active distributed RC network which, by using dominant poles and zeros, realizes a very accurate approximation of an arbitrary ...
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 ...
A compound Poisson distribution is the sum of independent and identically distributed random variables over a count variable that follows a Poisson distribution. Generally, this distribution is not ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback