Hierarchical Structure Recovery of Point‐Sampled Surfaces

We focus on the class of ‘regular’ models defined by Várady et al. for reverse engineering purposes. Given a 3D surface represented through a dense set of points, we present a novel algorithm that converts to a hierarchical representation . In , the surface is encoded through patches of various shape and size, which form a hierarchical atlas. If belongs to the class of regular models, then captures the most significant features of at all the levels of detail. In this case, we show that can be exploited to interactively select regions of interest on and intuitively re‐design the model. Furthermore, intrinsically encodes a hierarchy of useful ‘segmentations’ of . We present a simple though efficient approach to extract and optimize such segmentations, and we show how they can be used to approximate the input point sets through idealized manifold meshes.     

An Efficient Algorithm for Determining an Aesthetic Shape Connecting Unorganized 2D Points

We present anefficient algorithm for determining an aesthetically pleasing shape boundary connecting all the points in a given unorganized set of 2D points, with no other information than point coordinates. By posing shape construction as a minimisation problem which follows the Gestalt laws, our desired shape is non‐intersecting, interpolates all points and minimizes a criterion related to these laws. The basis for our algorithm is an initial graph, an extension of the Euclidean minimum spanning tree but with no leaf nodes, called as the minimum boundary complex . and can be expressed similarly by parametrizing a topological constraint. A close approximation of , termed can be computed fast using a greedy algorithm. is then transformed into a closed interpolating boundary in two steps to satisfy ’s topological and minimization requirements. Computing exactly is an NP (Non‐Polynomial)‐hard problem, whereas is computed in linearithmic time. We present many examples showing considerable improvement over previous techniques, especially for shapes with sharp corners. Source code is available online.     

Enhancing Bayesian Estimators for Removing Camera Shake

The aim of removing camera shake is to estimate a sharp version x from a shaken image y when the blur kernel k is unknown. Recent research on this topic evolved through two paradigms called and . only solves for k by marginalizing the image prior, while recovers both x and k by selecting the mode of the posterior distribution. This paper first systematically analyses the latent limitations of these two estimators through Bayesian analysis. We explain the reason why it is so difficult for image statistics to solve the previously reported failure. Then we show that the leading methods, which depend on efficient prediction of large step edges, are not robust to natural images due to the diversity of edges. , although much more robust to diverse edges, is constrained by two factors: the prior variation over different images, and the ratio between image size and kernel size. To overcome these limitations, we introduce an inter‐scale prior prediction scheme and a principled mechanism for integrating the sharpening filter into . Both qualitative results and extensive quantitative comparisons demonstrate that our algorithm outperforms state‐of‐the‐art methods.     

Application of generally weighted moving average method to tracking signal state space model

In predicting time series, if a trend includes a structural break, then a state space model can be applied to revise the predictive method. Some scholars suggest that restricted damped trend models yield excellent prediction results by automatically revising unforeseen structural break factors in the prediction process. Restricted damped trend models add a smoothed error statistic to a local‐level model and use the exponentially weighted moving average (EWMA) method to make corrections. This paper applies the generally weighted moving average (GWMA) concept and method to a restricted damped trend model that changes the smoothed error statistic from the EWMA form to the GWMA form and adds the correction parameter λ, which distinguishes three situations , , and . The original restricted damped trend model applies only to , enabling the model to capture situations in which and increases its generality. This paper also compares the effect of various parameter values on the predictive model and finds the range of parameter settings that optimize the model.     

Weighted control with ‐stability constraint for switched positive linear systems

This paper is concerned with the problem of control with ‐stability constraint for a class of switched positive linear systems. The ‐stability means that all the poles of each subsystem of the resultant closed‐loop system belong to a prescribed disk in the complex plane. A sufficient condition is derived for the existence of a set of state‐feedback controllers, which guarantees that the closed‐loop system is not only positive and exponentially stable with each subsystem ‐stable but also has a weighted performance for a class of switching signals with average dwell time greater than a certain positive constant. Both continuous‐time and discrete‐time cases are considered, and all of the obtained conditions are formulated in terms of linear matrix inequalities, whose solution also yields the desired controller gains and the corresponding minimal average dwell time. Numerical examples are given to illustrate the effectiveness of the presented approach.Copyright © 2012 John Wiley & Sons, Ltd.     

Determinization and minimization of finite acyclic automata by incremental techniques

The determinization of a nondeterministic finite automaton (FA) is the process of generating a deterministic FA (DFA) equivalent to (sharing the same regular language of) . The minimization of is the process of generating the minimal DFA equivalent to . Classical algorithms for determinization and minimization are available in the literature for several decades. However, they operate monolithically, assuming that the FA to be either determinized or minimized is given once and for all. By contrast, we consider determinization and minimization in a dynamic context, where augments over time: after each augmentation, determinization and minimization of into is required. Using classical monolithic algorithms to solve this problem is bound to poor performance. An algorithm for incremental determinization and minimization of acyclic finite automata, called IDMA, is proposed. Despite being conceived within the narrow domain of model‐based diagnosis and monitoring of active systems, the algorithm is general‐purpose in nature. Experimental evidence indicates that IDMA is far more efficient than classical algorithms in solving incremental determinization and minimization problems. Copyright © 2015 John Wiley & Sons, Ltd.     

Dual approaches to strictly positive real controller synthesis with a performance using linear matrix inequalities

The synthesis of controllers that minimize a performance index subject to a strictly positive real (SPR) constraint is considered. Two controller synthesis methods are presented that are then combined into an iterative algorithm. Each method synthesizes optimal SPR controllers by posing a convex optimization problem where constraints are enforced via linear matrix inequalities. Additionally, each method fixes the controller state‐feedback gain matrix and finds an observer gain matrix such that an upper bound on the closed‐loop ‐norm is minimized and the controller is SPR. The first method retools the standard ‐optimal control problem by using a common Lyapunov matrix variable to satisfy both the criteria and the SPR constraint. The second method overcomes bilinear matrix inequality issues associated with the performance and the SPR constraint by employing a completing the square method and an overbounding technique. Both synthesis methods are used within an iterative scheme to find optimal SPR controllers in a sequential manner. Comparison of our synthesis methods to existing methods in the literature is presented. Copyright © 2012 John Wiley & Sons, Ltd.     

Remarks on the relationship between stability and internal stability of nonlinear systems

In this paper, we investigate the relationship between stability and internal stability of nonlinear systems. It is shown that under certain conditions, stability implies attractivity of the equilibrium and that local stability with finite gain implies local asymptotic stability of the origin. Copyright © 2012 John Wiley & Sons, Ltd.     

A generic static analyzer for multithreaded Java programs

In this paper, we present heckmate , the first generic static analyzer of multithreaded Java programs based on abstract interpretation. heckmate can be tuned at different levels of precision and efficiency in order to prove various properties (e.g., absence of divisions by zero and data races), and it is sound for multithreaded programs. It supports all the most relevant features of Java multithreading, such as dynamic thread creation, runtime creation of monitors, and dynamic allocation of memory. The experimental results demonstrate that heckmate is accurate and efficient enough to analyze programs with some thousands of statements and a potentially infinite number of threads. Copyright © 2012 John Wiley & Sons, Ltd.     

Greedy Geometric Algorithms for Collection of Balls,with Applications to Geometric Approximation and Molecular Coarse‐Graining

Choosing balls that best approximate a 3D object is a non‐trivial problem. To answer it, we first address the inner approximation problem, which consists of approximating an object defined by a union of n balls with balls defining a region . This solution is further used to construct an outer approximation enclosing the initial shape, and an interpolated approximation sandwiched between the inner and outer approximations. The inner approximation problem is reduced to a geometric generalization of weighted max k‐cover, solved with the greedy strategy which achieves the classical lower bound. The outer approximation is reduced to exploiting the partition of the boundary of by the Apollonius Voronoi diagram of the balls defining the inner approximation. Implementation‐wise, we present robust software incorporating the calculation of the exact Delaunay triangulation of points with degree two algebraic coordinates, of the exact medial axis of a union of balls, and of a certified estimate of the volume of a union of balls. Application‐wise, we exhibit accurate coarse‐grain molecular models using a number of balls 20 times smaller than the number of atoms, a key requirement to simulate crowded cellular environments.     

Full complexity analysis of the diameter‐constrained reliability

Let be a simple graph with nodes and links, a subset of “terminals,” a vector , and a positive integer d, called “diameter.” We assume that nodes are perfect but links fail stochastically and independently, with probabilities . The “diameter‐constrained reliability” (DCR) is the probability that the terminals of the resulting subgraph remain connected by paths composed of d links, or less. This number is denoted by . The general DCR computation belongs to the class of ‐hard problems, since it subsumes the problem of computing the probability that a random graph is connected. The contributions of this paper are twofold. First, a full analysis of the computational complexity of DCR subproblems is presented in terms of the number of terminal nodes and the diameter d. Second, we extend the class of graphs that accept efficient DCR computation. In this class, we include graphs with bounded co‐rank, graphs with bounded genus, planar graphs, and, in particular, Monma graphs, which are relevant to robust network design.     

Stability control and recurrent switching rules

Recently, it has been enlightened the interest of a class of switching rules with good properties, which are called eventually periodic: more precisely, it has been proven that a finite family of linear vector fields of can be stabilized by means of eventually periodic switching rules provided that it is asymptotically controllable and satisfies an additional finite time controllability condition. Unfortunately, simple examples point out that in general, eventually periodic switching rules are not robust with respect to state measurement errors. In this paper, we introduce a new type of switching rules with improved robustness properties, which are called recurrent switching rules. They are subject to the construction of a finite sequence of complete cones Γ₁, … ,Γ_H of . We shown that, if a stabilizing eventually periodic switching rule for is known, then Γ₁, … ,Γ_H can be constructed in such a way that is stabilized by any recurrent switching rule subject to Γ₁, … ,Γ_H. Copyright © 2012 John Wiley & Sons, Ltd.     

On computing the 2‐diameter ‐constrained K ‐reliability of networks

This article considers a communication network modeled by a graph and a distinguished set of terminal nodes . We assume that the nodes never fail, but the edges fail randomly and independently with known probabilities. The classical K ‐reliability problem computes the probability that the subnetwork is composed only by the surviving edges in such a way that all terminals communicate with each other. The d ‐diameter ‐constrained K ‐reliability generalization also imposes the constraint that each pair of terminals must be the extremes of a surviving path of approximately d length. It allows modeling communication network situations in which limits exist on the acceptable delay times or on the amount of hops that packets can undergo. Both problems have been shown to be NP ‐hard, yet the complexity of certain subproblems remains undetermined. In particular, when , it was an open question whether the instances with were solvable in polynomial time. In this paper, we prove that when and is a fixed parameter (i.e. not an input) the problem turns out to be polynomial in the number of nodes of the network (in fact linear). We also introduce an algorithm to compute these cases in such time and also provide two numerical examples.     

The Mixed Robust /FTS Control Problem Analysis and State Feedback Control

In this paper we deal with the mixed  /finite‐time stability control problem. More specifically, given an open loop uncertain linear system, we provide a necessary and sufficient condition for quadratic input‐output finite‐time stability with an  bound. Exploiting this result we also give a sufficient condition to solve the related synthesis problem via state‐feedback. The property of quadratic input‐output finite‐time stability with an  bound implies that the system under consideration satisfies an  performance bound between the disturbance input and the controlled output and, at the same time, is input‐output finite‐time stable for all admissible uncertainties. This condition requires the solution of a feasibility problem constrained by a pair of differential linear matrix inequalities (LMIs) coupled with a time‐varying LMI. The proposed technique is illustrated by means of both a numerical and a physical example.     

A safe variant of the unsafe integer arithmetic of Java™

Computers are finite machines and, therefore, the arithmetic operations in a programming language are different from their mathematical counterparts. These restrictions seem not to have been, in general, fully appreciated in programming languages and in computer science textbooks. One example is the programming language Java, which makes it difficult to warn the user in cases in which arithmetic operations produce incorrect results. In this paper we look at integer arithmetic in Java and develop a safe variant of the arithmetic operations in Java. The design of the safe variant of , , , , and for the types byte , short , int and long reveals a number of deficiencies of Java in integer arithmetic, floating point arithmetic and program structure. Some of these deficiencies are also present in other contemporary programming languages. The paper therefore ends with some proposals for the design of the arithmetic elements of programming languages. Copyright © 2002 John Wiley & Sons, Ltd.     

Polynomial time approximation algorithms for proportionate open‐shop scheduling

This paper deals with the presentation of polynomial time (approximation) algorithms for a variant of open‐shop scheduling, where the processing times are only machine‐dependent. This variant of scheduling is called proportionate scheduling and its applications are used in many real‐world environments. This paper develops three polynomial time algorithms for the problem. First, we present a polynomial time algorithm that solves the problem optimally if , where n and m denote the numbers of jobs and machines, respectively. If, on the other hand, , we develop a polynomial time approximation algorithm with a worst‐case performance ratio of that improves the bound existing for general open‐shops. Next, in the case of , we take into account the problem under consideration as a master problem and convert it into a simpler secondary approximation problem. Furthermore, we formulate both the master and secondary problems, and compare their complexity sizes. We finally present another polynomial time algorithm that provides optimal solution for a special case of the problem where .     

Graphical tuning method of FOPID controllers for fractional order uncertain system achieving robust ‐stability

This paper focuses on the graphical tuning method of fractional order proportional integral derivative (FOPID) controllers for fractional order uncertain system achieving robust ‐stability. Firstly, general result is presented to check the robust ‐stability of the linear fractional order interval polynomial. Then some alternative algorithms and results are proposed to reduce the computational effort of the general result. Secondly, a general graphical tuning method together with some computational efficient algorithms are proposed to determine the complete set of FOPID controllers that provides ‐stability for interval fractional order plant. These methods will combine the results for fractional order parametric robust control with the method of FOPID ‐stabilization for a fixed plant. At last, two important extensions will be given to the proposed graphical tuning methods: determine the ‐stabilizing region for fractional order systems with two kinds of more general and complex uncertainty structures: multi‐linear interval uncertainty and mixed‐type uncertainties. Numerical examples are followed to illustrate the effectiveness of the method. Copyright © 2015 John Wiley & Sons, Ltd.     

Quantized filtering for Markovian jump LPV systems with intermittent measurements

This paper investigates the problem of quantized filtering for a class of discrete‐time linear parameter‐varying systems with Markovian switching under data missing. The measured output of the plant is quantized by a logarithmic mode‐independent quantizer. The data missing phenomenon is modeled by a stochastic variable. The purpose of the problem addressed is to design a full‐order filter such that the filtering error dynamics is stochastically stable and the prescribed noise attenuation level in the sense can be achieved. Sufficient conditions are derived for the existence of such filters in terms of parameterized linear matrix inequalities. Then the corresponding filter synthesis problem is transformed into a convex optimization problem that can be efficiently solved by using standard software packages. A simulation example is utilized to demonstrate the usefulness of the developed theoretical results. Copyright © 2011 John Wiley & Sons, Ltd.     

Spline Based Pseudo‐Inversion of Sampled Data Non‐Minimum Phase Systems for an Almost Exact Output Tracking

This paper considers the problem of achieving a very accurate tracking of a pre‐specified desired output trajectory , for linear, multiple input multiple output, non‐minimum phase and/or non hyperbolic, sampled data, and closed loop control systems. The proposed approach is situated in the general framework of model stable inversion and introduces significant novelties with the purpose of reducing some theoretical and numerical limitations inherent in the methods usually proposed. In particular, the new method does not require either a preactuation or null initial conditions of the system. The desired and the corresponding sought input are partitioned in a transient component ( and u_t(k), respectively) and steady‐state ( and u_s(k), respectively). The desired transient component is freely assigned without requiring it to be null over an initial time interval. This drastically reduces the total settling time. The structure of u_t(k) is a priori assumed to be given by a sampled smoothing spline function. The spline coefficients are determined as the least‐squares solution of the over‐determined system of linear equations obtained imposing that the sampled spline function assumed as reference input yield the desired output over a properly defined transient interval. The steady‐state input u_s(k) is directly analytically computed exploiting the steady‐state output response expressions for inputs belonging to the same set of .