نتایج جستجو برای: backward differentiation formula
تعداد نتایج: 339033 فیلتر نتایج به سال:
This paper presents a fast frontal face detection method. We use motion segmentation algorithm that makes use of differencing to detect moving people’s faces. The novelty of this paper comes from the differencing in real time input images, preprocessing to remove noises (morphological operator and so on), detecting edge lines and restoration, finding the face area and cutting the head candidate...
In this paper we introduce and study a new complexity measure for finite words. For positive integer d special scattered subwords, called super-d-subwords, in which the gaps are of length at least (d−1), are defined. We give methods to compute super-d-complexity (the total number of different super-d-subwords) in the case of rainbow words (with pairwise different letters) by recursive algorithm...
We present a class of semi-implicit finite element (FE) schemes that uses arbitrary Lagrangian Eulerian methods (ALE) to solve the incompressible Navier–Stokes equations (NSE) on time varying domains. We use the kth order backward differentiation formula (BDFk) and Taylor– Hood Pm/Pm−1 finite elements. The well-known telescope formulas of BDFk have been extended from k = 1, 2 to k = 3, 4, 5. Th...
The importance of good estimates of the defect in the numerical solution of initial value problem ordinary differential equations is considered in the context of global error estimation by using adjoint-equation based methods. In the case of solvers based on the fixed leading coefficient backward differentiation formulae, the quality of defect estimates is shown to play a major role in the reli...
In this work we deal with the numerical solution of the fluid-structure interaction problem arising in the haemodynamic environment. In particular, we consider BDF and Newmark time discretization schemes, and we study different methods for the treatment of the fluid-structure interface position, focusing on partitioned algorithms for the prescription of the continuity conditions at the fluid-st...
Abstract : — Block Digital Filtering (BDF) is a well known method for fast digital ltering. Indeed, it decomposes the input signal into blocks and takes pro t of complexity reduction provided by the Fast Fourier Transform algorithm to considerably reduce the computational cost. In this paper, we propose a simple and ef cient matrixoriented approach to compute and visualize the frequency respons...
We study the backward shift operator on Hilbert spaces Hα (for α ≥ 0) which are norm equivalent to the Dirichlet-type spaces Dα. Although these operators are unitarily equivalent to the adjoints of the forward shift operator on certain weighted Bergman spaces, our approach is direct and completely independent of the standard Cauchy duality. We employ only the classical Hardy space theory and an...
We study a class of explicit or implicit multistep integration formulas for solving N X N systems of ordinary differential equations. The coefficients of these formulas are diagonal matrices of order N, depending on a diagonal matrix of parameters Q of the same order. By definition, the formulas considered here are exact with respect to y = Dy + 4>(x, y) provided Q — hD, h is the integration st...
Exponential integrators have been introduced as an efficient alternative to explicit and implicit methods for integrating large stiff systems of differential equations. Over the past decades these methods have been studied theoretically and their performance was evaluated using a range of test problems. While the results of these investigations showed that exponential integrators can provide si...
In the paper the relation is given between linear difference equations with constant coefficients those obtained via the application of forward and backward differences. Relation is also established between input-output difference equations and state-space difference equations, which define the state of inner quantities of a discrete system. In conclusion, the state-space representation of a di...
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