Exploratory data analysis for planar tessellations: Structural analysis and point process methods

This paper presents methods for the exploratory analysis of particular geometrical data, namely planar tessellations. At first, two non-stochastic methods are suggested which may help to classify tessellations and to understand their structure. The first one consists of approximating a given tessellation by a Dirichlet tessellation. The other one uses the nodes of a given tessellation and tests the possibility of reconstructing it by a fixed rule of connecting nodes by edges. Furthermore, in order to obtain information on the spatial behaviour of a tessellation, we suggest the use of the methods of point process statistics. In particular, pair correlation and mark correlation functions describe spatial correlations in tessellations.     

Stability of interconnected impulsive systems with and without time delays,using Lyapunov methods

In this paper, we consider the input-to-state stability (ISS) of impulsive control systems with and without time delays. We prove that, if the time-delay system possesses an exponential Lyapunov–Razumikhin function or an exponential Lyapunov–Krasovskii functional, then the system is uniformly ISS provided that the average dwell-time condition is satisfied. Then, we consider large-scale networks of impulsive systems with and without time delays and prove that the whole network is uniformly ISS under the small-gain and the average dwell-time condition. Moreover, these theorems provide us with tools to construct a Lyapunov function (for time-delay systems, a Lyapunov–Krasovskii functional or a Lyapunov–Razumikhin function) and the corresponding gains of the whole system, using the Lyapunov functions of the subsystems and the internal gains, which are linear and satisfy the small-gain condition. We illustrate the application of the main results on examples.     

奇数维可压缩液晶流方程解的逐点估计

首先, 本文利用标准的能量估计方法得到高维(3 维及以上) 的液晶流方程组小初值经典解的整体存在性. 然后, 本文运用Green 函数方法, 得到奇数维情形(3 维及以上) 该解的逐点估计. 该结果表明, 密度ρ和动量m同Navier-Stokes 方程组一样满足一般Huygens 原理, 而单位向量场d则没有这种现象, 其有着与热方程的解类似的时空估计.     

Explicit solutions of generalized Cauchy-Riemann systems using the transplant operator

In Kravchenko (2008) [8] it was shown that the tool introduced there and called the transplant operator transforms solutions of one Vekua equation into solutions of another Vekua equation, related to the first via a Schrödinger equation. In this paper we prove a fundamental property of this operator: it preserves the order of zeros and poles of generalized analytic functions and transforms formal powers of the first Vekua equation into formal powers of the same order for the second Vekua equation. This property allows us to obtain positive formal powers and a generating sequence of a “complicated” Vekua equation from positive formal powers and a generating sequence of a “simpler” Vekua equation. Similar results are obtained regarding the construction of Cauchy kernels. Elliptic and hyperbolic pseudoanalytic function theories are considered and examples are given to illustrate the procedure.     

Studying discrete dynamical systems through differential equations

In this paper we consider dynamical systems generated by a diffeomorphism F defined on U an open subset of Rn, and give conditions over F which imply that their dynamics can be understood by studying the flow of an associated differential equation, , also defined on U. In particular the case where F has n−1 functionally independent first integrals is considered. In this case X is constructed by imposing that it shares with F the same set of first integrals and that the functional equation μ(F(x))=det(DF(x))μ(x), x∈U, has some non-zero solution, μ. Several examples for n=2,3 are presented, most of them coming from several well-known difference equations.     

Influence of nonmagnetic impurities on superconductivity in two-band systems with variable charge carrier densities

Two-band superconductors with a nonmagnetic impurity are considered in the framework of perturbation theory. Analytical expressions are obtained for the temperature of the superconductivity transition T_C and the order parameters Δ_n (n=1,2) at different values of the charge carrier density (chemical potential μ). An impurity introduced into the system can influence T_C and Δ_n in two ways: it can lead to a change in μ and can cause inter-band scattering by the impurity potential. These mechanisms can either cancel each other or destroy the superconductivity. Here a significant role is played by the occupation of the energy bands, by which superconductivity can be completely suppressed by the nonmagnetic impurity. Translated from Teoreticheskaya i Matematicheskaya Fizika, Vol. 111, No. 2, pp. 289–303, May, 1997.     

Unbiased identification of a class of multi-input single-output systems with correlated disturbances using bias compensation methods

This paper studies the modelling and identification problems for multi-input single-output (MISO) systems with colored noises. In order to obtain the unbiased recursive estimates of the systems, this paper presents a recursive least squares (RLS) identification algorithm based on bias compensation technique. The basic idea is to eliminate the estimation bias by adding a correction term in the least squares (LS) estimates, a set of stable digital prefilters are suitably designed to preprocess the input sampled data from multi-input channels for the purpose of getting the bias term arisen by colored noises in LS estimates, and further to derive a bias compensation based RLS algorithm. The performance of the developed method is both analyzed theoretically and shown by means of simulation results.     

Studying an overload system using rotation

1. IntroductionThe motivation of writing this paper was from calculating the blocking probability foran overloaded finite system. Our numerical experiments suggested that this probability canbe approximated efficiently by rotating the transition matrix by 180". Some preliminaryresults were obtained and can be found in [11 and [2]. Rotating the transition matrix definesa new Markov chain, which is often called the dual process in the literature, for example,[3--7]. For a finite Markov chain, …     

Stabilization methods for systems with two linear delays

In this paper we obtain stabilization methods for some systems with two linear delays. We present a numerical example which illustrates the effectiveness of one of stabilization methods.     

Differential systems with semi-stable equilibria and numerical methods

Summary. In this paper the (long time) stability of numerical methods for a class of nonlinear autonomous differential systems possessing a semi-stable equilibrium, is considered. The local dynamics of the class under the H-assumptions is reviewed. Some interesting differential systems of stiff type are seen to belong to this class. It is also shown that the Implicit Euler method is the only one of practical interest which is unconditionally stable. Mathematics Subject Classification (2000):65L20, 47H10, 37G05     

Identification of MIMO systems using radial basis function networks with hybrid learning algorithm

When a radial basis function network (RBFN) is used for identification of a nonlinear multi-input multi-output (MIMO) system, the number of hidden layer nodes, the initial parameters of the kernel, and the initial weights of the network must be determined first. For this purpose, a systematic way that integrates the support vector regression (SVR) and the least squares regression (LSR) is proposed to construct the initial structure of the RBFN. The first step of the proposed method is to determine the number of hidden layer nodes and the initial parameters of the kernel by the SVR method. Then the weights of the RBFN are determined by solving a simple minimization problem based on the concept of LSR. After initialization, an annealing robust learning algorithm (ARLA) is then applied to train the RBFN. With the proposed initialization approach, one can find that the designed RBFN has few hidden layer nodes while maintaining good performance. To show the feasibility and superiority of the annealing robust radial basis function networks (ARRBFNs) for identification of MIMO systems, several illustrative examples are included.     

Dissipativity of Runge-Kutta methods for dynamical systems with delays

This paper is concerned with the numerical solution of dissipativeinitial value problems with delays by Runge-Kutta methods. Asufficient condition for the dissipativity of the systems isgiven. The concepts of D(l)-dissipativity and GD(l)-dissipativityare introduced. We investigate the dissipativity propertiesof (k,l)-algebraically stable Runge-Kutta methods with piecewiseconstant or linear interpolation procedures for finite-dimensionaland infinite-dimensional dynamical systems with delays.     

Bias compensation methods for stochastic systems with colored noise

For ARX-like systems, this paper derives a bias compensation based recursive least squares identification algorithm by means of the prefilter idea and bias compensation principle. The proposed algorithm can give the unbiased estimates of the system model parameters in the presence of colored noises, and can be on-line implemented. Finally, the advantages of the proposed bias compensation recursive least squares algorithm are shown by simulation tests.     

A-stability of Runge-Kutta methods for systems with additive noise

Numerical stability of both explicit and implicit Runge-Kutta methods for solving ordinary differential equations with an additive noise term is studied. The concept of numerical stability of deterministic schemes is extended to the stochastic case, and a stochastic analogue of Dahlquist'sA-stability is proposed. It is shown that the discretization of the drift term alone controls theA-stability of the whole scheme. The quantitative effect of implicitness uponA-stability is also investigated, and stability regions are given for a family of implicit Runge-Kutta methods with optimal order of convergence.This author was partially supported by the Italian Consiglio Nazionale delle Ricerche.     

The Three-Dimensional ℤ2 Electrodynamics and the Two-Dimensional Ising Model

We calculate the correlation functions for the three-dimensional ₂ electrodynamics for particular values of the interaction energies and with free boundary conditions.     

Mathematical study of two-variable systems with adaptive numerical methods

In this paper, we consider reaction–diffusion systems arising from two-component predator–prey models with Smith growth functional response. The mathematical approach used here is in two folds since the time-dependent partial differential equations consist of both linear and nonlinear terms. We discretize the stiff or moderately stiff term with the fourth-order difference operator and advance the resulting nonlinear system of ordinary differential equations with the two competing families of the exponential time differencing (ETD) schemes, and we analyze them for stability. Numerical comparison between these two methods for solving various predator–prey population models with functional responses are also presented. Numerical results show that the techniques require less computational work. Also in the numerical results, some emerging spatial patterns are unveiled.     

Optimal load sharing in soft real-time systems using likelihood ratios

We consider a load-sharing problem for a multiprocessor system in which jobs have real-time constraints: if the waiting time of a job exceeds a given random amount (called the laxity of the job), then the job is considered lost. To minimize the steady-state probability of loss with respect to the load-sharing parameters, we propose to use the likelihood ratio derivative estimate approach, which has recently been studied for sensitivity analysis of stochastic systems. We formulate a recursive stochastic optimization algorithm using likelihood ratio estimates to solve the optimization problem and provide a proof for almost sure convergence of the algorithm. The algorithm can be used for on-line optimization of the real-time system and does not require a priori knowledge of the arrival rate of customers to the system or the service time and laxity distributions. To illustrate our results, we provide simulation examples.This research was partially supported by an IBM Graduate Fellowship and by the National Science Foundation through Grant No. ECS-87-15217.     

Preconditioning for radial basis functions with domain decomposition methods

In our previous work, an effective preconditioning scheme that is based upon constructing least-squares approximation cardinal basis functions (ACBFs) from linear combinations of the RBF-PDE matrix elements has shown very attractive numerical results. The preconditioner costs O(N²) flops to set up and O(N) storage. The preconditioning technique is sufficiently general that it can be applied to different types of different operators. This was applied to the 2D multiquadric method, with c~1/√N on the Poisson test problem, the preconditioned GMRES converges in tens of iterations. In this paper, we combine the RBF methods and the ACBF preconditioning technique with the domain decomposition method (DDM). We studied different implementations of the ACBF-DDM scheme and provide numerical results for N > 10,000 nodes. We shall demonstrate that the efficiency of the ACBF-DDM scheme improves dramatically as successively finer partitions of the domain are considered.