一类Feistel密码的线性分析

该文提出一种新的求取分组密码线性偏差上界的方法，特别适用于密钥线性作用的Feistel密码．该分析方法的思路是，首先对密码体制线性偏差进行严格的数学描述，分别给出密码线性偏差与轮函数F及S盒的线性偏差的数学关系；然后通过求取线性方程组最小重量解，确定密码线性偏差的上界．     

插补法CAI研究

数字程序控制计算机辅助教学是将计算机技术用于数字程序控制的教学过程，它帮助学生学习并模拟教学实验．本文介绍了数字程序控制中直线插补和圆孤插补的ＣＡＩ实现方法．     

COATES GRAPH APPROACH FOR GENERATING SYMBOLIC NETWORK FUNCTION

In this paper, symbolic code matrix ,constant matrix and count matrix are defined .The first twomatrices are used to describe the elemental expression of augmented matrix and the nede admittance equa-tion is thus obtained. The third matrix is used to obtain the incoming degree matrix, and according to thematrix all the 1- factors of the Coates graph are given. By using the data code, the determinant is expandedand the same items in the expansion are merged. Thus the symbolic network function in which no term can-cellation occurs is generated.     

Average consensus in networks of dynamic agents with switching topologies and multiple time-varying delays

In this paper, we discuss average consensus problem in undirected networks of dynamic agents with fixed and switching topologies as well as multiple time-varying communication delays. By employing a linear matrix inequality method, we prove that all the nodes in the network achieve average consensus asymptotically for appropriate communication delays if the network topology is connected. Particularly, several feasible linear matrix inequalities are established to determine the maximal allowable upper bound of time-varying communication delays. Numerical examples are given to demonstrate the effectiveness and the sharpness of the theoretical results.     

VaR and ES for linear portfolios with mixture of elliptic distributions risk factors

In this paper, we generalize the Linear VaR method from portfolios with normally distributed risk factors to portfolios with mixture of elliptically distributed ones. We treat both the Expected Shortfall and the Value-at-Risk of such portfolios. Special attention is given to the particular case of a mixture of multivariate t-distributions. This is a part of J. SADEFO-KAMDEM PhD Thesis[12] of the Université de Reims, France . It has been presented at the workshop on modelling and computation in Financial Engineering at Bad Herrenalb, Germany May 6-8, 2003. The author is an associate professor at the Department of mathematics, université d’Evry Val d’Essonne.     

Response level crossing rate of a linear system excited by a partially specified Gaussian load process

The problem of determining the maximum mean response level crossing rate of a linear system driven by a partially specified Gaussian load process has been considered. The partial specification of the load is given only in terms of its total average energy. The critical input power spectral (PSD) function, which maximizes the mean response level crossing rate, is obtained. The critical input PSD turns out to be highly narrow-banded which fails to capture the erratic nature of the excitation. Consequently, the trade-off curve between the maximum mean response level crossing rate and the maximum disorder in the input process, quantified in terms of its entropy rate, has been generated. The method of Pareto optimization is used to tackle the conflicting objectives of the simultaneous maximization of the mean response level crossing rate and the input entropy rate. The non-linear multi-objective optimization has been carried out using a recently developed multi-criteria genetic algorithm scheme. Illustrative example of determining the critical input of an axially vibrating rod, excited by a partially specified stationary Gaussian load process, has been considered.     

Interaction bounds in multivariable control systems

Time-domain limitations due to right half-plane zeros and poles in linear multivariable control systems are studied. Lower bounds on the interaction are derived. They show not only how the location of zeros and poles are critical in multivariable systems, but also how the zero and pole directions influence the performance. The results are illustrated on the quadruple-tank process, which is a new multivariable laboratory process.     

A dynamic linear programming approach to market allocation of renewable resources in the italian energy system: The case of solar thermal and biogas technologies

In Italy solar thermal energy and energy from biogas are two possible means of reducing dependence on energy imports. Using a multiperiod LP model (MARKAL) the authors assessed the likely potential of both technologies under various circumstances. The study covered the period 1980–2005, in five segments of five years. It focused only on the subsystem of the energy end-uses which can be substituted for by solar thermal and biogas technologies. The overall non-renewable sources which can be saved in 20 years by these technologies total 450 PJ (1 PJ = 10^{1 5} J) if the fuel prices rise at 0 per cent average annual, 1450 PJ if the fuel prices rise at 4.2 per cent average annual, 1860 PJ if the fuel prices rise at 7.2 per cent average annual and 3780 PJ if the fuel prices rise at 15 per cent average annual. However the most competitive technologies appear to be solar water heaters used mainly in the private and commercial sectors and biogas systems used mainly in the agricultural sector. The study was carried out by APRE under ENEA (formerly CNEN) contract and was intended to serve as an analytical basis for establishing an overall development and demonstration strategy for end-use renewable technologies in Italy.     

Extensions of LDA by PCA mixture model and class-wise features

Linear discriminant analysis (LDA) is a data discrimination technique that seeks transformation to maximize the ratio of the between-class scatter and the within-class scatter. While it has been successfully applied to several applications, it has two limitations, both concerning the underfitting problem. First, it fails to discriminate data with complex distributions since all data in each class are assumed to be distributed in the Gaussian manner. Second, it can lose class-wise information, since it produces only one transformation over the entire range of classes. We propose three extensions of LDA to overcome the above problems. The first extension overcomes the first problem by modelling the within-class scatter using a PCA mixture model that can represent more complex distribution. The second extension overcomes the second problem by taking different transformation for each class in order to provide class-wise features. The third extension combines these two modifications by representing each class in terms of the PCA mixture model and taking different transformation for each mixture component. It is shown that all our proposed extensions of LDA outperform LDA concerning classification errors for synthetic data classification, hand-written digit recognition, and alphabet recognition.     

Wake and aerodynamics loads in multiple bodies—application to turbomachinery blade rows

Two-dimensional, unsteady flow around bodies of complex geometry (or multiple bodies) at high Reynolds number is simulated using the vortex method. This method is modified to take into account the sub-grid scale phenomena through a second order velocity structure function model adapted to the Lagrangian scheme. The dynamics of the body wake is computed using the convection-diffusion splitting algorithm; the convection process is carried out with a Lagrangian Adams-Bashforth time-marching scheme and the diffusion process is simulated using the random walk method. The pressure distribution is obtained using an integral equation derived from the pressure Poisson equation, which was first developed for a single body. Results for the numerical simulation around a linear cascade of airfoils are presented. As the flow is periodic in the y direction, the discrete vortex shedding need only be considered for a reference airfoil. The flow characteristics around the NACA 65-410 series airfoils are calculated and comparisons are made with results available in the literature.