查看更多>>摘要：The aim of this article is to provide an improvement in the reconstruction and visualization of retinal superficial capillary plexus and choriocapillaris images from healthy subjects. The implemented method uses multiple Optical Coherence Tomography (OCT) scanned sequences, performs a registration, an average and a filtering on them using for this last step the Sampling Kantorovich operator (SK). The resulting images are then analyzed with some well known methods in literature to quantitatively evaluate the improvement achieved by the proposed technique. Also fluoroangiography and histological images are introduced as reference to support the reliability and the goodness of the results. (C) 2022 Elsevier Inc. All rights reserved.
查看更多>>摘要：In this paper, we extensively study the orthogonal spline collocation method known as the spline collocation at Gauss points with Rannacher's time-marching scheme for free boundary value option pricing problems. Such financial problems commonly feature non-smooth payoff functions that cause inaccuracies in approximating the solution and its derivatives. As a result, unlike the problems with the smooth initial data, the quadratic convergence is not realized by the Crank-Nicolson time-stepping scheme for these problems. Furthermore, the non-smoothness in the initial condition leads to severe degradation in the convergence rates and spurious oscillations near the discontinuity. The rationale is that classical schemes strongly rely on the smoothness of the initial data. A rigorous time-marching scheme referred to as Rannacher time-stepping scheme is introduced for the American option's price diagnosed by a linear complementarity problem to smoothen the data. Moreover, with careful analysis, second and fourth orders of convergence are established for the present scheme in temporal and spatial directions, respectively. The numerical results for three test problems are presented in tables and graphs to validate the theory. These results show that the present scheme achieves higher accuracy and sufficiently restores the expected behavior. (C) 2022 Elsevier Inc. All rights reserved.
查看更多>>摘要：We present an implicit Split-Step explicit Euler type Method (dubbed SSM) for the simulation of McKean-Vlasov Stochastic Differential Equations (MV-SDEs) with drifts of super linear growth in space, Lipschitz in measure and non-constant Lipschitz diffusion coefficient. The scheme is designed to leverage the structure induced by the interacting particle approximation system, including parallel implementation and the solvability of the implicit equation. The scheme attains the classical 1 / 2 root mean square error (rMSE) convergence rate in stepsize and closes the gap left by [1] regarding efficient implicit methods and their convergence rate for this class of McKean-Vlasov SDEs. A sufficient condition for mean-square contractivity of the scheme is presented. Several numerical examples are presented, including a comparative analysis to other known algorithms for this class (Taming and Adaptive time-stepping) across parallel and non-parallel implementations.(c) 2022 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )
查看更多>>摘要：This paper investigates the leader-following quasi-bipartite synchronization problem of coupled heterogeneous harmonic oscillators under an undirected communication topology. To save limited resources and alleviate communication burden, two asynchronous event triggered protocols are proposed. Some sufficient criteria are derived to ensure quasi bipartite synchronization by utilizing differential equation theory, inequality theory and Lyapunov stability method. Meanwhile, it is shown that there is no Zeno behavior for the proposed event-triggered protocols. Furthermore, an upper bound of quasi-bipartite synchronization errors is explicitly provided. Finally, numerical examples are given to illustrate the effectiveness of the theoretical results. (C) 2022 Elsevier Inc. All rights reserved.
查看更多>>摘要：This paper proposes a new method based on the polynomial expansions for structural uncertainty analysis. A generalized finite difference method (GFDM) based on the Taylor expansion is adopted to compute the structural responses, which has good adaptabilities to the analysis domains due to its meshless property. With the help of the polynomial chaos expansions (PCE), random variables subjected to any probability distribution are implicitly quantified. The GFDMPCE method combines GFDM and PCE, is verified by the classical Monte Carlo method (MCM) in terms of calculation accuracy and efficiency. This method is non-intrusive, rigorous in mathematical theory, and shows bright prospects for the robust analysis of large-scale and complex structures.
查看更多>>摘要：In this paper, the fixed-time adaptive tracking control issues of the nonlinear systems with input quantization are considered. By designing a common adaptive parameter, the overparameterization problem of the most existing results is resolved. Based on command filter and backstepping technique, the fixed-time adaptive tracking control can be first realized. In addition, we adopt the Nussbaum-type function to deal with the quantized input. The fuzzy logic systems are utilized to approximate the unknown nonlinearlities. Moreover, it can be concluded that the proposed method can guarantee the stability of the controlled system and the boundedness of the whole signals. At last, simulation examples are employed to verify the availability of the presented scheme.(c) 2022 Elsevier Inc. All rights reserved.
查看更多>>摘要：Let D = (V, A) be a digraphs without isolated vertices. The first Zagreb index of a digraph D is definedas asummationover allarcs, M 1(D) = 1/2 Sigma(uv is an element of A)(d(u)(+) + d(v)(-)), where d(u)(+) (resp. d(u)(-)) denotes the out-degree (resp. in-degree) of the vertex u. In this paper, we give the maximal values and maximal digraphs of first Zagreb index over the set of all orientations of unicyclic graphs with n vertices and matching number m (2 <= m <= left pernpedicularn 2right pernpedicular). (C) 2022 Elsevier Inc. All rights reserved.
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