Testing the robust Schur stability of a segment of complex polynomials

Given two Schur stable complex polynomials p 0 ( z ) and p 1 ( z ) of the same degree n, we present a procedure for testing if convex combinations of the form (1 - u ) p 0 ( z ) + u p 1 ( z ) are Schur stable for all u ] [0, 1]. The procedure consists in constructing a polynomial array, which corresponds to the process of extracting the greatest common divisor of two polynomials, and testing the absence of real zeros of a real u polynomial of degree 2 n for u ] (0, 1). Since the latter task can be finished by using the Sturm theorem, the proposed procedure for testing the robust Schur stability of a segment of complex polynomials is efficient in the sense that it accomplishes the test in a finite number of arithmetic operations. As the derivation given in this paper establishes a connection between our procedure and Bose's resultant method, and identifies an intrinsic simplification for the latter method, the presented procedure can be viewed as an efficient algorithmic implementation of Bose's resultant method for testing the robust Schur stability of complex segment polynomials.     

TVD finite point method for two-dimensional conservation equation

A new meshless method, called total variation diminishing (TVD) finite point method (TVDFP), is proposed. The TVDFP method is developed on the least-square procedure which uses a global stencil of grid points and the two-dimensional (2D) TVD procedure for the approximation of fictitious interface directional fluxes. We present the accuracy of the TVDFP method and several 2D test computations.     

A clustering procedure for exploratory mining of vector time series

A two-step procedure is developed for the exploratory mining of real-valued vector (multivariate) time series using partition-based clustering methods. The proposed procedure was tested with model-generated data, multiple sensor-based process data, as well as simulation data. The test results indicate that the proposed procedure is quite effective in producing better clustering results than a hidden Markov model (HMM)-based clustering method if there is a priori knowledge about the number of clusters in the data. Two existing validity indices were tested and found ineffective in determining the actual number of clusters. Determining the appropriate number of clusters in the case that there is no a priori knowledge is a known unresolved research issue not only for our proposed procedure but also for the HMM-based clustering method and further development is necessary.     

Chaos control of performance measure approach for evaluation of probabilistic constraints

Performance measure approach (PMA) is a recently proposed method for evaluation of probabilistic constraints in reliability-based design optimization of structure. The advanced mean-value (AMV) method is well suitable for PMA due to its simplicity and efficiency. However, when the AMV iterative scheme is applied to search for the minimum performance target point for some nonlinear performance functions, the iterative sequences could fall into the periodic oscillation and even chaos. In the present paper, the phenomena of numerical instabilities of AMV iterative solutions are illustrated firstly. And the chaotic dynamics analysis on the iterative procedure of AMV method is performed. Then, the stability transformation method of chaos feedback control is suggested for the convergence control of AMV procedure in the parameter interval in which the iterative scheme fails. Numerical results of several nonlinear performance functions demonstrate that the control of periodic oscillation, bifurcation and chaos for AMV iterative procedure is achieved, and the stable convergence solutions are obtained.     

Support vector censored quantile regression under random censoring

Censored quantile regression models have received a great deal of attention in both the theoretical and applied statistical literature. In this paper, we propose support vector censored quantile regression (SVCQR) under random censoring using iterative reweighted least squares (IRWLS) procedure based on the Newton method instead of usual quadratic programming algorithms. This procedure makes it possible to derive the generalized approximate cross validation (GACV) method for choosing the hyperparameters which affect the performance of SVCQR. Numerical results are then presented which illustrate the performance of SVCQR using the IRWLS procedure.     

一种基于FCMAC神经网络的优化方法

提出了一种利用FCMAC(Fuzzy Cerebellar Model Articulation Controller)神经网络进行优化的方法。该方法由学习过程和优化过程两部分组成。对于许多没有模型可参考的实际过程，使用该方法只需要传感器的观测信息就能进行优化。仿真结果证明了该方法的有效性与优越性，进而提出了在实际应用中进行优化的一种方案。     

A method for auto-tuning of PID control parameters

A method for automatic tuning of the PID process control parameters, usually called ‘auto-tuning’, is developed. The procedure of applying the method consists of (1) sampling a process response to a test input signal, (2) processing the sampled data for estimating characteristic values of the process, and (3) calculating the optimal values of the PID control parameters. For the optimization, a new type of performance index, i.e. a weighted integral of squared error is introduced. The procedure is implemented on a digital controller using microprocessors and applied to some real processes, yielding satisfactory results.     

A method for partial-fraction expansion of transfer matrices

A general method for partial-fraction expansion of transfer matrices is presented and a general formula is given. The main ideas of the procedure include: (1) no required derivatives for the case of repeated eigenvalues: (2) all the matrix residues are found at the same time; and (3) there is no need for knowledge of the minimal polynomial. The procedure can be easily applied to digital computer application and fills a void in the computer method for finding the partial-fraction expansion in the case of repeated eigenvalues. The results are presented in structured form using Kronecker products in a way that facilitates easy implementation using a variety of standard software packages     

An integrated genetic algorithm complemented with direct search for optimum design of RC frames

This paper presents an improved optimum design method for reinforced concrete (RC) frames using an integrated genetic algorithm (GA) with a direct search method. A conventional genetic algorithm occasionally has limitations due to a low convergence rate in spite of high computing times. The proposed method in this research uses a predetermined section database (DB) when determining trial sections for the next iteration.From an initial section determined by substituting calculated member forces into a regression formula, a direct search that determines a final discrete solution is followed within a limited range in the section database. Due to the fast convergence and the sequential determination of feasible trial sections close to the final optimum solution, an introduction of the search procedure at each iteration allows difficulties to be solved during the application of a conventional GA to large RC structures.Finally, the effectiveness of the introduced design procedure is verified through correlative tests of the introduced design procedure.     

Analysis and synthesis of a class of discrete-time neural networksdescribed on hypercubes

A qualitative analysis is presented for a class of synchronous discrete-time neural networks defined on hypercubes in the state space. Analysis results are utilized to establish a design procedure for associative memories to be implemented on the present class of neural networks. To demonstrate the storage ability and flexibility of the synthesis procedure, several specific examples are considered. The design procedure has essentially the same desirable features as the results of J. Li et al. (1988, 1989) for continuous-time neural networks. For a given system dimension, networks designed by the present method may have the ability to store more patterns (as asymptotically stable equilibria) than corresponding discrete-time networks designed by other techniques. The design method guarantees the storage of all the desired patterns as asymptotically stable equilibrium points. The present method provides guidelines for reducing the number of spurious states and for estimating the extent of the patterns' domains of attraction. The present results provide a means of implementing neural networks by serial processors and special digital hardware.     

基于UIO的协议测试序列生成方法的改进

文章在FSM模型下基于UIO序列的协议测试生成算法的基础上,介绍了UIO(S)序列和IO(S,K)序列的生成算法.并针对在IUT中,会出现UIO(S)和IO(S,K)序列失效的问题,提出了一种有效的检验方法.最后,给出了完整的测试序列生成方法.     

Second Chebyshev wavelet operational matrix of integration and its application in the calculus of variations

In this paper, we extend the application of the second Chebyshev wavelet (SCW) method to solve variational problems and establish a clear solving procedure for this kind of problems. An operational matrix of integration based on the SCW is presented and a general procedure for forming this matrix is given. The main characteristic of SCW operational matrix method is that it can transform a variational problem to a system of algebraic equations. Thus, it can simplify the variational problems solving. The proposed method is illustrated by some applications, which can show the validity of the present approach.     

Symbolic agglomerative clustering for quantitative analysis of remotely sensed data

An efficient nonparametric, hierarchical, symbolic agglomerative clustering procedure based on the mutual nearest neighbourhood concept is proposed for classifying remotely sensed multispectral data. The procedure utilized a data reduction technique and an innovative symbolic concept to minimize the memory and computational time requirements. A new non-metric similarity measure and a novel method of formulation of composite symbolic objects are proposed to enrich the performance of the algorithm. A Mean Difference Index (MDI) concept for identifying the optimal number of classes was used. Experiments were conducted on IRS (Indian Remote Sensing) satellite data to authenticate the efficacy of the procedure.     

一种基于T矩阵的10项误差模型SOLT校准方法

采用基于波传播矩阵（T-Matrix）的10项误差模型对三通道二端口矢量网络分析仪（Vector network analy-zer,VNA）进行短路-开路-匹配-直通（SOLT）校准,校准过程中只需计算并保存两个特征变量,即可推导出二端口待测件（Device Under Test,DUT）的T矩阵,进而得到待测件（DUT）的散射矩阵。与传统的SOLT校准相比,这种算法不必计算各个系统误差项,DUT的散射矩阵直接由校准和测试过程中的散射参数测量值表示得到。最后,利用此方法计算二端口待测件的真实散射参数,并与传统的SOLT算法进行对比,其结果吻合良好。     

论反标架方法对多变量系统鲁棒性设计的改进

Macfarlane等提出的反标架方法(Reversed-Frame-Nomalizing)是适用于多变量系统鲁 棒性CAD的频域方法,这一方法是基于矩阵赋值函数的奇异值分解.本文在介绍这一方法 的基础上,着重讨论反标架方法对系统鲁棒性设计的改进,并对该方法中分频段补偿器的设计 提出了改进建议.通过数值例子说明这一方法较逆奈氏阵列法与特征轨迹法对系统鲁棒稳定 性设计具有的优越性,也说明了这一方法在PC机上的可实现性.     

基于神经网络的宽带相干DOA估计方法的改进

相干信号子空间处理方法(CSM)是一种通过构造聚焦(focusing)矩阵来估计宽带 相干源波达方向(DOA)的有效方法.基于逆传播(Back-propagation)学习算法.对神经网 络实现聚焦过程的方法进行了网络结构及模式的改进,使网络可以在未知波达方向个数时完 成聚焦过程;同时,使学习空间从D(DOA个数)维降为1维,大大地简化了学习过程,加速了 网络的收敛过程.     

基于BPEL4WS的Web服务整合研究

业务流程执行语言（BPEL4WS）是整合Web 服务的标准，其作用是将一组现有的服务整合起来，从而定义一个新的 Web 服务。首先介绍了业务流、工作流、以及BPEL4WS在Web服务建模方面的基本概念，建立了BPEL4WS整合Web服务模型，提出了组合服务的方法和过程。最后通过实例证明了BPEL4WS服务整合的实用性。     

Service process control: a method to compare dynamic robustness of alternative service processes

This paper contributes to the service engineering field by developing a procedure to compare the dynamic robustness of alternative service delivery processes. The procedure adapts an existing method for comparing the dynamic robustness of chemical process control systems. It has four steps: (a) characterisation of each type of uncertainty that affects the service plant; (b) Monte Carlo computer simulation of the process flowchart to determine how the service process responds to different combinations of uncertainties; (c) calculation of a quality index for each combination of uncertainties; and (d) plotting of a frequency distribution of these indices. The tighter the resulting distribution, the more robust the system. The procedure can be used to evaluate the effects of design and control changes in the service delivery process. To demonstrate the procedure, a modification to a hospital patient-treatment process is evaluated.     

Border-tracing algorithm implementation for the femoral geometry reconstruction

In some orthopaedic applications such as the design of custom-made hip prostheses, reconstruction of the bone morphology is a fundamental step. Different methods are available to extract the geometry of the femoral medullary canal from computed tomography (CT) images. In this research, an automatic procedure (border-tracing method) for the extraction of bone contours was implemented and validated. A composite replica of the human femur was scanned and the CT images processed using three different methods, a manual procedure; the border-tracing algorithm; and a threshold-based method. The resulting contours were used to estimate the accuracy of the implemented procedure. The two software techniques were more accurate than the manual procedure. Then, these two procedures were applied to an in vivo CT data set in order to determine to most critical region for repeatability. Only for the images located in this region, the repeatability measurement was carried out for six in vivo CT data sets to evaluate the inter-femur repeatability. The border-tracing method was found to achieve the highest repeatability.     

The discontinuous Galerkin method with Lax–Wendroff type time discretizations

In this paper we develop a Lax–Wendroff time discretization procedure for the discontinuous Galerkin method (LWDG) to solve hyperbolic conservation laws. This is an alternative method for time discretization to the popular total variation diminishing (TVD) Runge–Kutta time discretizations. The LWDG is a one step, explicit, high order finite element method. The limiter is performed once every time step. As a result, LWDG is more compact than Runge–Kutta discontinuous Galerkin (RKDG) and the Lax–Wendroff time discretization procedure is more cost effective than the Runge–Kutta time discretizations for certain problems including two-dimensional Euler systems of compressible gas dynamics when nonlinear limiters are applied.