EEorts to develop sinc domain decomposition methods for second-order two-point boundary-value problems have been successful, thus warranting further development of these methods. A logical rst step is to thoroughly investigate the extension of these methods to Poisson's equation posed on a rectangle. The Sinc-Galerkin and sinc-collocation methods are, for appropriate weight choices, identical f...

Perceived blur is an important measure of image quality and clinical visual function. The magnitude of image blur varies across space and time under natural viewing conditions owing to changes in pupil size and accommodation. Blur is frequently studied in the laboratory with a variety of digital filters, without comparing how the choice of filter affects blur perception. We examine the percepti...

In this paper a data simulation system, based on the cos(x) and sin(x)/x functions, called CSINC Polynomial Higher Order Neural Network (CSINCPHONN) has been developed. The CSINCPHONN model provides one more opportunity to find the optimal neural network model for simulation and prediction. This paper also proves that CSINCPHONN models can converge when simulating XOR data. This study also test...

Abstract An efficient direct domain decomposition method is developed coupled with Poly-Sinc approximation over complex geometry. We solve 2D Poisson equations in L-Shaped geometry. The spatial domains of interest are decomposed into several non-overlapping rectangular subdomains. In each sub-domain, a Poly-Sinc collocation scheme is used to approximate the solution of the governing equation. S...

Contents Abstract Sinc approximation methods excel for problems whose solutions may have singularities, or innnite domains, or boundary layers. This article summarizes results obtained to date, on Sinc numerical methods of computation. Sinc methods provide procedures for function approximation over bounded or unbounded regions, encompassing interpolation, approximation of derivatives, approxima...

A number of problems in image reconstruction and image processing can be addressed, in principle, using the sinc kernel. Since the sinc kernel decays slowly, however, it is generally avoided in favor of some more local but less precise choice. In this paper, we describe the fast sinc transform, an algorithm which computes the convolution of arbitrarily spaced data with the sinc kernel in O.N lo...