A tabu search method for geometric primitive extraction

In this paper, we propose a novel method for extracting the geometric primitives from geometric data, which is essentially an optimization problem. Specifically, we use tabu search to solve geometric primitive extraction problem. To the best of our knowledge, it is the first attempt that tabu search is used in computer vision. Our tabu search (TS) has a number of advantages: (1) TS avoids entrapment in local minima and continues the search to give a near-optimal final solution; (2) TS is very general and conceptually much simpler than either simulated annealing (SA) or genetic algorithm (GA); (3) TS has no special space requirement and is very easy to implement (the entire procedure only occupies a few lines of code); (4) our TS-based method can successfully extract some geometric primitives which are specially difficult for the traditional methods such as Hough Transform (HT) and Robust Statistics (RS). TS is a flexible framework of a variety of strategies originating from artificial intelligence and is therefore open to further improvement.     

Switching through singularities

Asymptotic tracking is studied for systems which are not regular, that is, the relative degree is not well defined. For these systems, the input–output linearizing control law has singularities. We propose a tracking control law which switches between an approximate tracking law (Hauser et al., IEEE Trans. Automat. Control 37 (3) (1992) 392–398) close to the singularities, and an exact tracking law away from the singularities, and we study the applicability of this law based on the behavior of the system’s zero dynamics at the switching boundary. As in Hauser et al. (IEEE Trans. Automat. Control 37 (3) (1992) 392–398), the ball and beam example is used to motivate the study.     

Continuous time-varying linear systems

We discuss implicit systems of ordinary linear differential equations with (time-) variable coefficients, their solutions in the signal space of hyperfunctions according to Sato and their solution spaces, called time-varying linear systems or behaviours, from the system theoretic point of view. The basic result, inspired by an analogous one for multidimensional constant linear systems, is a duality theorem which establishes a categorical one–one correspondence between time-varying linear systems or behaviours and finitely generated modules over a suitable skew-polynomial ring of differential operators. This theorem is false for the signal spaces of infinitely often differentiable functions or of meromorphic (hyper-)functions or of distributions on . It is used to obtain various results on key notions of linear system theory. Several new algorithms for modules over rings of differential operators and, in particular, new Gröbner basis algorithms due to Insa and Pauer make the system theoretic results effective.     

Measuring texture classification algorithms

The texture analysis literature lacks a widely accepted method for comparing algorithms. This paper proposes a framework for comparing texture classification algorithms. The framework consists of several suites of texture classification problems, a standard functionality for algorithms, and a method for computing a score for each algorithm. We use the framework to demonstrate the peaking phenomenon in texture classification algorithms. The framework is publicly available on the Internet.     

A skew-symmetric property of rigid-body systems

The configuration space for the attitude of a vehicle can be modeled as SO(3), namely the rotation matrix group. This work investigates the globally valid dynamics of natural Lagrangian systems and gyroscopic systems with configuration space including SO(3). The dynamics is derived by using the global representations of jet bundles of SO(3). A skew-symmetric property associated with the systems can be then established. Such property can be used in many applications such as the adaptive controller design.     

Continuity properties of balanced realizations

In this paper topological and geometrical properties of pre-balanced and balanced realizations are considered. It is shown that analytic pre-balancing coordinate transformations do exist and that the set of pre-balanced realizations forms an analytic submanifold. Explicit formulas for the tangent spaces and their dimension are derived. Continuity properties of balanced realizations are studied. For systems with more than two inputs and two outputs explicit points of discontinuity of balancing coordinate transformations are described. A certain class of balancing coordinate transformations is shown to be discontinuous, even for distinct and fixed singular values.     

Inheritance rules for flexible model retrieval

Convenient model management requires flexible model retrieval. This paper presents a new flexible retrieval approach for mathematical model bases. The approach defines a multi-valued model inheritance relationship among models at a signature level. The inheritance provides a rich semantic information for the retrieval mechanism to refine inexact retrieval requirements. An inheritance rules reasoning system is proposed to enhance the ability and the efficiency of the model retrieval. The interface of the approach includes an SQL-like command, which enables users to retrieve their required models with inexact requirement expressions. The approach has been implemented in a rule-based mathematical model base system RMMBS. Application examples demonstrate the retrieval approach.     

Model reduction for state-space symmetric systems

In this paper, the model reduction problem for state-space symmetric systems is investigated. First, it is shown that several model reduction methods, such as balanced truncation, balanced truncation which preserves the DC gain, optimal and suboptimal Hankel norm approximations, inherit the state-space symmetric property. Furthermore, for single input and single output (SISO) state-space symmetric systems, we prove that the H_∞ norm of its transfer functions can be calculated via two simple formulas. Moreover, the SISO state-space symmetric systems are equivalent to systems with zeros interlacing the poles (ZIP) under mild conditions.     

Exploring cache performance in multithreaded processors

Multithreading is a well known technique to hide latency in a non-blocking cache architecture. By switching execution from one thread to another, the CPU can perform useful work, while waiting for pending requests to be processed by the main memory. In this paper we examine the effects of varying the associativity and block size on cache performance in a reduced locality of reference environment, due to multithreading. We find that for associativity equal to the number of threads, the cache produces very low miss rate even for small sizes. Also by taking into account the increase in cycle time due to larger cache size or associativity we find that the optimum cache configuration for best processor performance is 16Kbytes direct mapped. Finally, with a constant main memory bandwidth, increasing the block size to more than 32 bytes, reduces the miss rate, but degrades processor performance.     

Summative evaluation of the SINCGARS Tutor

In an earlier set of studies with a different Intelligently Coached Simulation (Orey, M.A., Fan, H., Park, J., Tzeng, S., & Gustafson, K. (1995). Evaluation of Device operator in a context of a coached simulation environment), we found a retention and a transfer problem. We tried to solve these problems while building a new Intelligently Coached Simulation (the SINCGARS Tutor). The solutions to the two problems were to use an interactive conceptual model for the retention problem and we used photographs of the equipment as the visuals of the simulation. We then tested this new tutor with a group of 22 officers who were not only required to know how to operate the SINCGARS radio, but would be responsible for teaching others in their unit when their training was complete. We had one group of officers train on the real equipment, in pairs, with one instructor available for guidance. The other group of 11 learned via the SINCGARS Tutor. The post test was to put an actual radio into operation while being observed by a trained observer. Results indicate that not only did the transfer problem go away, but officers trained on the computer performed the task more accurately both initially on the immediate post test and again on a surprise four-week delayed post test. The SINCGARS Tutor was found to be a very good training solution.     

Order statistics and probabilistic robust control

Order statistics theory is applied in this paper to probabilistic robust control theory to compute the minimum sample size needed to come up with a reliable estimate of an uncertain quantity under continuity assumption of the related probability distribution. Also, the concept of distribution-free tolerance intervals is applied to estimate the range of an uncertain quantity and extract the information about its distribution. To overcome the limitations imposed by the continuity assumption in the existing order statistics theory, we have derived a cumulative distribution function of the order statistics without the continuity assumption and developed an inequality showing that this distribution has an upper bound which equals to the corresponding distribution when the continuity assumption is satisfied. By applying this inequality, we investigate the minimum computational effort needed to come up with an reliable estimate for the upper bound (or the lower bound) and the range of a quantity. We also give conditions, which are much weaker than the absolute continuity assumption, for the existence of such minimum sample size. Furthermore, the issue of making tradeoff between performance level and risk is addressed and a guideline for making this kind of tradeoff is established. This guideline can be applied in general without continuity assumption.     

A learning result for continuous-time recurrent neural networks

The following learning problem is considered, for continuous-time recurrent neural networks having sigmoidal activation functions. Given a “black box” representing an unknown system, measurements of output derivatives are collected, for a set of randomly generated inputs, and a network is used to approximate the observed behavior. It is shown that the number of inputs needed for reliable generalization (the sample complexity of the learning problem) is upper bounded by an expression that grows polynomially with the dimension of the network and logarithmically with the number of output derivatives being matched.     

Receding horizon control via Bolza-type optimization

This paper deals with the stabilization problem of nonlinear control systems. A variant of the receding horizon control method is proposed which is based on the solution of a certain Bolza problem. The stabilizing property of the method is proved in the case of Lipschitz continuous value function. This version of receding horizon scheme can be considered as a straightforward generalization of the so-called Fake Riccati Equation Technique for nonlinear constrained systems.     

Constrained stabilization via smooth Lyapunov functions

We consider the problem of stabilizing a dynamic system by means of bounded controls. We show that the largest domain of attraction can be arbitrarily closely approximated by a “smooth” domain of attraction for which we provide an analytic expression. Such an expression allows for the determination of a (non-linear) control law in explicit form.     

Designing communication strategies for heterogeneous parallel systems

This paper explores the suitability of the emerging passive star-coupled optical interconnection using wavelength division multiplexing as the system interconnect to provide high bandwidth (Gbits/sec) communication demanded by heterogeneous systems. Several different communication strategies (combinations of communication topologies and protocols) are investigated under a representative master-slave computational model. The interplay between system speed, network speed, task granularity, and degree of parallelism is studied using both analytical modeling and simulations. It is shown that a hierarchical ALOHA-based communication strategy between the master and the slaves, implemented on top of the passive star-coupled network, leads to a considerable reduction in channel contention and provides 50–80% reduction in task completion time for applications with medium to high degrees of coarse grain parallelism. Comparable reduction in channel contention is also shown to be achieved by using tunable acoustooptic filters at master nodes.     

Coprimeness properties of nonlinear fractional system realizations

In this paper, the relationship between the Bezout and the set-theoretic approaches to left coprimeness is studied. It is shown that left coprimeness in the set-theoretic sense implies left coprimeness in the Bezout sense. In addition to these results, we investigate whether some properties for linear left coprime realizations carry over to the nonlinear case, for example we examine the relations between two left coprime realizations of the same system.     

Ergodic control of partially observed Markov chains

The ergodic or long-run average cost control problem for a partially observed finite-state Markov chain is studied via the associated fully observed separated control problem for the nonlinear filter. Dynamic programming equations for the latter are derived, leading to existence and characterization of optimal stationary policies.     

Transputer-based robot control system for six-joint robot manipulators

A transputer-based robot control system was designed and built to control an industrial robot PUMA 560. The goal was to develop a research tool for the investigation of practical and theoretical aspects of various advanced control strategies in the robot system. A transputer network consisting of thirteen transputers is employed for the application, where the parallelization of the algorithms is utilized for speeding up the computation. The kinematics, path planning and a collision avoidance module associated with a vision system are implemented on the network. Six joint controller modules were designed and constructed to handle input/output signals from the joint motors of the robot manipulator. The advanced multitransputer structure is capable of integrating the extern sensor information in a simple way and implementing control algorithms in parallel processes. For Software development, the parallel programming language Occam is used. The code development is performed on an IBM-PC-based toolset system.     

Robust stability of uncertain stochastic differential delay equations

In this paper we first discuss the robust stability of uncertain linear stochastic differential delay equations. We then extend the theory to cope with the robust stability of uncertain semi-linear stochastic differential delay equations. We shall also give several examples to illustrate our theory.