A time-domain adaptive algorithm was developed for solving elasto-dynamics problems through a mixed meshless local Petrov-Galerkin finite volume method (MLPG5). In this time-adaptive algorithm, each time-dependent variable is interpolated by time series function of n-order, which determined criterion in step. The high-order expanded variables bring high accuracy the domain, especially elasto-dy...

Digital image watermarking is an important technique for the authentication of multimedia content and copyright protection. Conventional digital image watermarking techniques are often vulnerable to geometric distortions such as Rotation, Scaling, and Translation (RST). These distortions desynchronize the watermark information embedded in an image and thus disable watermark detection. To solve ...

We recently reported on a method for measuring orbital angular momentum (OAM) states of light based on the transformation of helically phased beams to tilted plane waves [Phys. Rev. Lett.105, 153601 (2010)]. Here we consider the performance of such a system for superpositions of OAM states by measuring the modal content of noninteger OAM states and beams produced by a Heaviside phase plate.

This paper proposes a subtractive geometry projection topology optimization approach to simulate the multi-axis machining process and remove material from initial design domain. Each geometric primitive is described by plane extrusion operation based on 2D closed cubic spline curve controlled boundary points. The reference for 3D can freely rotate translate in space optimization. then projected...

Abstract This paper proposes a novel density-based method for structural design considering restrictions of multi-axis machining processes. A new mathematical formulation based on Heaviside function is presented to transform the field into geometry which can be manufactured by process. The developed 5-axis machining, also applied 2.5D milling restriction. filter techniques are incorporated effe...

In Lp-spaces with p an integer from [1, infinity) there exists a best approximation mapping to the set of functions computable by Heaviside perceptron networks with n hidden units; however for p an integer from (1, infinity) such best approximation is not unique and cannot be continuous.

We estimate variation with respect to half-spaces in terms of "flows through hyperplanes". Our estimate is derived from an integral representation for smooth compactly supported multivariable functions proved using properties of the Heaviside and delta distributions. Consequently we obtain conditions which guarantee approximation error rate of order O by one-hidden-layer networks with n sigmoid...

The contribution is focused on multiple change point detection in a onedimensional stochastic process by sparse parameter estimation from an overparametrized model. Stochastic process with changes in the mean is estimated using dictionary consisting of Heaviside functions. The basis pursuit algorithm is used to get sparse parameter estimates. Some properties of mentioned method are studied by s...