改进的多模式匹配算法

在有限自动机的多模式匹配算法（DFSA算法）的基础上，结合Quick Search算法的优点，提出了一个快速的多模式字符串匹配算法，之后在算法中以连续跳跃的思想，给出了另一个更加有效的改进，在一般情况下，这两个算法不需要匹配目标文本串中的每个字符，并充分利用了匹配过程是本次匹配不成功的信息，跳过尽可能多的字符，在模式串较长和较短的情况下，算法都有很好的性能，实验表明，在模式串较短时，所提出的算法需要的匹配时间仅为DFSA算法的1／2到1／5，在模式串较长时，所需时间为DFSA算法的1／3至1／7。     

软件测试技术的探讨

本文探讨了软件测试的若干关键技术，包括单元测试过程及优化、测试准则，测试技术和方法等，并根据自己的测试实践讨论了某型号项目应用软件测试中出现的问题。     

Robust control of uncertain distributed delay systems with application to the stabilization of combustion in rocket motor chambers

The problems of robust stability and robust stabilization of uncertain linear systems with distributed delay occurring in the state variables are studied in this paper. The essential requirement for the uncertainties is that they are norm-bounded with known bounds. Conditions for the robust stability of distributed time delay systems are given and a design method for the robust stabilizing control law of the uncertain systems is presented. The proposed method is applied to the stabilization of combustion in the chamber of a liquid monopropellant rocket motor. It is found that the combustion can be robustly stabilized when the two parameters pressure exponent γ and maximal time lag r vary in specified intervals, respectively.     

On the equivalence of causal LTI iterative learning control and feedback control

The goal of iterative learning control (ILC) is to improve the accuracy of a system that repeatedly follows a reference trajectory. This paper proves that for each causal linear time-invariant ILC, there is an equivalent feedback that achieves the ultimate ILC error with no iterations. Remarkably, this equivalent feedback depends only on the ILC operators and hence requires no plant knowledge. This equivalence is obtained whether or not the ILC includes current-cycle feedback. If the ILC system is internally stable and converges to zero error, there exists an internally stabilizing feedback that approaches zero error at high gain. Since conventional feedback requires no iterations, there is no reason to use causal ILC.     

On maximum induced matchings in bipartite graphs

The problem of finding a maximum induced matching is known to be NP-hard in general bipartite graphs. We strengthen this result by reducing the problem to some special classes of bipartite graphs such as bipartite graphs with maximum degree 3 or C₄-free bipartite graphs. On the other hand, we describe a new polynomially solvable case for the problem in bipartite graphs which deals with a generalization of bi-complement reducible graphs.     

Parallel distance transforms on a linear array architecture

Distance transformation (DT) has been widely used for image matching and shape analysis. In this paper, a parallel algorithm for computing distance transformation is presented. First, it is shown that the algorithm has an execution time of 6N−4 cycles, for an N×N image using a parallel architecture that requires ⌈N/2⌉ parallel processors. By doing so, the real time requirement is fulfilled and its execution time is independent of the image contents. In addition, a partition method is developed to process an image when the parallel architecture has a fixed number of processing elements (PEs); say two or more. The total execution time for an N×N image by employing a fixed number of PEs is 2[N²/M+2(M−1)], when M is the fixed number of PEs.     

Asymptotically optimal smoothing of averaged LMS estimates for regression parameter tracking

The sequence of estimates formed by the LMS algorithm for a standard linear regression estimation problem is considered. It is known since earlier that smoothing these estimates by simple averaging will lead to, asymptotically, the recursive least-squares algorithm. In this paper, it is first shown that smoothing the LMS estimates using a matrix updating will lead to smoothed estimates with optimal tracking properties, also in case the true parameters are slowly changing as a random walk. The choice of smoothing matrix should be tailored to the properties of the random walk. Second, it is shown that the same accuracy can be obtained also for a modified algorithm, SLAMS, which is based on averages and requires much less computations.     

The infinite time near optimal decentralized regulator problem for singularly perturbed systems: a convex optimization approach

This paper presents LQ decentralized pole location for singularly perturbed systems. The poles are located in a sector included in the left-half complex plane. The singular perturbation method is used to define reduced and well-behaved problems. It is shown that the LQ control problem with pole location in a sector can be solved using the LMI tool. The associated parametrical optimization problem involves a linear cost objective under LMI constraints. The decentralized control problem is then solved in the reduced slow system by just introducing structure constraints on the matrix variables, constraints that do not destroy the linearity and then the convexity of the problem.     

Flatness tolerance evaluation: an approximate minimum zone solution

This paper is concerned with the problem of flatness tolerance evaluation. First, we introduce the concepts of width and inner radius of point sets, and establish the equivalence between the width of a point set and the inner radius of the convex hull of the self-difference of the set. On this basis, we present an algorithm for calculating the exact minimum zone tolerance of flatness. Second, we prove that an approximation of the inner radius of a convex set can be obtained from the inner radius of the set in fixed direction. On this basis, we present an algorithm for calculating the ‘almost exact’ minimum zone solution. This algorithm is implemented by solving a single linear programming problem, of which the computational complexity is O(n). Numerical examples are given to validate the proposed algorithms.     

Mbius立方体上一个新圈的构造算法

Mbius立方体上一个新圈的构造算法@刘昕$青岛大学信息工程学院!山东青岛266071 @王庆红$青岛大学信息工程学院!山东青岛266071 @樊建席$青岛大学信息工程学院!山东青岛266071~~~~