This proposed paper presents architecture of generalized recursive function to generate approximation of orthogonal function DCT with an approximate length N could be derived from a pair of DCTs of length (N/2) at the cost of N additions for input preprocessing. Approximation of DCT is useful for reducing its computational complexity without impact on its coding performance. Most of the existin...

We study the evolution of the mass autocorrelation function by describing the growth of density fluctuations through the Zel’dovich approximation. The results are directly compared with the predictions of the scaling hypothesis for clustering evolution extracted from numerical simulations (Hamilton et al. 1991), as implemented by Jain, Mo & White (1995). We find very good agreement between the ...

A scheme is proposed for the numerical study of optimal control problems related to groundwater quality management in case nonpoint-source pollution. The corresponding state equation a system coupled nonlinear partial differential equations. approximation given by finite volume based on two-point flux with upwind mobilities embedded an iterative fixed point approximation. analysis convergence a...

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In this paper our aim is to estimate integrals of the form [,"if} = J~... f(ei9)dl-£(8) where 1-£ is, in general a complex measure. We consider quadrature formulas like [n if} = L:7=1 Aj,nf(xj,n) with n distinct nodes Xj,n on the unit circle and so that [,"if} = [n{f} for any f E 'Rn (a certain subspace of Laurent polynomials with dimension n). Under appropriate assumptions on the function f we...

For a set P of n points in the unit ball b ⊆ Rd, consider the problem of finding a small subset T ⊆ P such that its convex-hull ε-approximates the convex-hull of the original set. Specifically, the Hausdorff distance between the convex hull of T and the convex hull of P should be at most ε. We present an efficient algorithm to compute such an ε′-approximation of size kalg, where ε′ is a functio...

Using moving parabolic approximations (MPA), we reconstruct an improved point-based model of curve or surface represented as an unorganized point cloud, while also estimating the differential properties of the underlying smooth manifold. We present optimization algorithms to solve these MPA models, and examples which show that our reconstructions of the curve or surface, and estimates of the no...