We investigated the formation of the aerial image in the double-pass method to measure the optical quality of the human eye. We show theoretically and empirically that the double pass through the eye's optics forces the light distribution in the aerial image to be an even-symmetric function even if the single-pass point-spread function is asymmetric as a result of odd aberrations in the eye. Th...

There is extensive mathematical literature on the inverse problem of deautoconvolution for a function with support in unit interval $[0,1] \subset \mathbb{R}$, but little known about multidimensional situation. This article tries to fill this gap analytical and numerical studies reconstruction real two variables over square from observations its autoconvolution $[0,2]^2 \mathbb{R}^2$ (full data...

using the mean-value theorem for integrals we tried to solved the nonlinear integral equations of hammerstein type . the mean approach is to obtain an initial guess with unknown coefficients for unknown function y(x). the procedure of this method is so fast and don't need high cpu and complicated programming. the advantages of this method are that we can applied for those integral equation...

Recent computer simulations suggest that the presence of aggregates of red blood cells (RBCs), at random angles and lengths, does not affect the measurements of blood flow transverse to the ultrasound (US) beam direction using a correlation-based method and an intravascular (IV) US array catheter. However, in case of aggregates of RBCs aligned with the flow, measurements of simulated blood velo...

Abstract In time series analysis, signal covariance modeling is an essential part of stochastic methods like prediction or filtering. geodetic applications, functions are rarely treated as true compactly supported although large amounts data would approve such. Covariance models for complex correlation shapes also rare. Ideally, general families with a flexibility desirable to model correlation...

This paper describes how realistic neuromorphic networks can have their connectivity fully characterized in analytical fashion. By assuming that all neurons have the same shape and are regularly distributed along the two-dimensional orthogonal lattice with parameter ∆, it is possible to obtain the exact number of connections and cycles of any length from the autoconvolution function as well as ...