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Nanjing, China

Nanjing Audit University is an accounting-focused university with its campus at Jianye, a district of Nanjing, China.The university was founded in 1983 and has emphasis on Economics and Management, with Law, Language and Literature, Science and Engineering. It is under the auspices of the Jiangsu Provincial Government, the China National Audit Office and the People's Bank of China.There are more than 22,000 students on two campuses covering 2200 acres: Mochou Campus, in the Jianye District of Nanjing, named after nearby Mochou Lake, and the Pukou Campus on the southern slope of Laoshan Mountain, a national forest and park. Wikipedia.

Wang T.,Nanjing University of Information Science and Technology | Guo B.,CAS Beijing Institute of Applied Physics And Computational Mathematics | Xu Q.,Nanjing Audit University
Journal of Computational Physics

In this paper, a fourth-order compact and energy conservative difference scheme is proposed for solving the two-dimensional nonlinear Schrödinger equation with periodic boundary condition and initial condition, and the optimal convergent rate, without any restriction on the grid ratio, at the order of O(h4 + τ2) in the discrete L2-norm with time step τ and mesh size h is obtained. Besides the standard techniques of the energy method, a new technique and some important lemmas are proposed to prove the high order convergence. In order to avoid the outer iteration in implementation, a linearized compact and energy conservative difference scheme is derived. Numerical examples are given to support the theoretical analysis. © 2013 Elsevier Inc. Source

In linear multi-input multi-output channel systems, reduction process is employed to reduce the computational cost of sphere decoding (SD) algorithm. Usually a reduction process includes not only permutations but also unimodular transformations. However, owing to the box-constraint, the current reduction strategies are limited to only permutations, which makes SD algorithm still very time-consuming. In this study a theoretical complexity analysis on SD algorithm is first proposed to show what kind of criteria a reduction process should pursue. Then a new reduction strategy which combines permutations with unimodular transformations is presented to obtain a better reduced detection problem. Simulation results showed that this new reduction strategy can make SD algorithm much more efficient than those reduction strategies with only permutations. © 2012 The Institution of Engineering and Technology. Source

Yang Y.,Nanjing Audit University | Yang Y.,Nanjing Southeast University | Wang Y.,Soochow University of China

Let the random vector (X,Y) follow a bivariate Sarmanov distribution, where X is real-valued and Y is nonnegative. In this paper we investigate the impact of such a dependence structure between X and Y on the tail behavior of their product Z = XY. When X has a regularly varying tail, we establish an asymptotic formula, which extends Breiman's theorem. Based on the obtained result, we consider a discrete-time insurance risk model with dependent insurance and financial risks, and derive the asymptotic and uniformly asymptotic behavior for the (in)finite-time ruin probabilities. © 2012 Springer Science+Business Media, LLC. Source

Liu L.,Nanjing Audit University
Physica A: Statistical Mechanics and its Applications

In this paper, we investigate cross-correlations between crude oil and agricultural commodity markets. Based on a popular statistical test proposed by Podobnik et al. (2009), we find that the linear return cross-correlations are significant at larger lag lengths and the volatility cross-correlations are highly significant at all of the lag lengths under consideration. Using a detrended cross-correlation analysis (DCCA), we find that the return cross-correlations are persistent for corn and soybean and anti-persistent for oat and soybean. The volatility cross-correlations are strongly persistent. Using a nonlinear cross-correlation measure, our results show that cross-correlations are relatively weak but they are significant for smaller time scales. For larger time scales, the cross-correlations are not significant. The reason may be that information transmission from crude oil market to agriculture markets can complete within a certain period of time. Finally, based on multifractal extension of DCCA, we find that the cross-correlations are multifractal and high oil prices partly contribute to food crisis during the period of 2006-mid-2008. © 2013 Elsevier B.V. All rights reserved. Source

Huang B.,Nanjing Audit University
Knowledge-Based Systems

Dominance interval-based fuzzy objective information systems are generalized models of single-valued fuzzy information systems. By introducing a graded dominance relation to dominance interval-valued fuzzy objective information systems, we establish a graded dominance interval-valued rough set model (RSM), which is mainly based on replacing the indiscernibility relation in classical rough set theory with the graded dominance interval-valued relation. Furthermore, in order to simplify knowledge representation and extract nontrivial simpler graded dominance interval fuzzy decision rules, we propose two attribute reduction approaches to eliminate the redundant condition attributes that are not essential from the viewpoint of graded dominance interval-valued fuzzy decision rules. These results are helpful for decision-making analysis in dominance interval-valued fuzzy objective information systems. © 2011 Elsevier B.V. All rights reserved. Source

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