Feedback stabilization for high order feedforward nonlinear time-delay systems

This paper investigates the problem of global strong stabilization by state feedback, for a family of high order feedforward nonlinear time-delay systems. The uncertain nonlinearities are assumed to satisfy a polynomial growth assumption with an input or delayed input dependent rate. With the help of the appropriate Lyapunov–Krasovskii functionals, and a rescaling transformation with a gain to be tuned online by a dynamic equation, we propose a dynamic low gain state feedback control scheme. A simulation example is given to demonstrate the effectiveness of the proposed design procedure.     

Versatile Tuning of Humanoid Agent Activity

In this paper, we present an integration framework for heterogeneous motion generators. The objective is to outline issues that are currently easily solved in professional post-processing systems used in film and game production but which cannot be transposed as is to real-time systems with autonomous agents. We summarise our approach for articulated agent-modelling and their animation by combining heterogeneous motion generators, such as real-time motion capturing, key-framing, inverse kinematics, procedural walking. We propose an agent/action-oriented framework. Activity properties such as action simultaneity and motion blending, spatial coherence, motion-flow update schemes, agent attachments, and location corrections, are the main topics handled by our generic animation framework. Numerous examples throughout the paper illustrate our approach and outline encountered problems and solutions or open research directions.     

Non-Linear Scale-Spaces Isomorphic to the Linear Case with Applications to Scalar,Vector and Multispectral Images

A basic requirement of scale-space representations in general is that of scale causality, which states that local extrema in the image should not be enhanced when resolution is diminished. We consider a special class of nonlinear scale-spaces consistent with this constraint, which can be linearised by a suitable isomorphism in the grey-scale domain so as to reproduce the familiar Gaussian scale-space. We consider instances in which nonlinear representations may be the preferred choice, as well as instances in which they enter by necessity. We also establish their relation to morphological scale-space representations based on a quadratic structuring function.     

Real-time range acquisition by adaptive structured light

The goal of this paper is to provide a "self-adaptive" system for real-time range acquisition. Reconstructions are based on a single frame structured light illumination. Instead of using generic, static coding that is supposed to work under all circumstances, system adaptation is proposed. This occurs on-the-fly and renders the system more robust against instant scene variability and creates suitable patterns at startup. A continuous trade-off between speed and quality is made. A weighted combination of different coding cues - based upon pattern color, geometry, and tracking - yields a robust way to solve the correspondence problem. The individual coding cues are automatically adapted within a considered family of patterns. The weights to combine them are based on the average consistency with the result within a small time-window. The integration itself is done by reformulating the problem as a graph cut. Also, the camera-projector configuration is taken into account for generating the projection patterns. The correctness of the range maps is not guaranteed, but an estimation of the uncertainty is provided for each part of the reconstruction. Our prototype is implemented using unmodified consumer hardware only and, therefore, is cheap. Frame rates vary between 10 and 25 fps, dependent on scene complexity.     

On the expected height of fringe-balanced trees

We study the effect of a well-known balancing heuristic on the expected height of a random binary search tree. After insertion of an element, if any node on the insertion path has a subtree of size precisely 2t+1 for a fixed integert, then the subtree rooted at that node is destroyed and replaced by a new subtree in which the median of the 2t+1 elements is the new root. IfH _n denotes the height of the resulting random tree, we show thatH _n /logn c(t) in probability for some functionc(t). In particular,c(0)=4.31107... (the ordinary binary search tree),c(1)=3.192570 ...,c(3)=2.555539 ...,c(10)=2.049289 ... andc(100)=1.623695 ....Research of the author was sponsored by NSERC Grant A3456 and by FCAR Grant 90-ER-0291     

A probabilistic analysis of the height of tries and of the complexity of triesort

Summary We consider binary tries formed by using the binary fractional expansions of X ₁, ...,X _n, a sequence of independent random variables with common density f on [0,1]. For H _n, the height of the trie, we show that either E(H_n)21og₂ n or E(H_n)= for all n2 according to whether f ²(x)dx is finite or infinite. Thus, the average height is asymptotically twice the average depth (which is log₂ n when f ²(x)dx>). The asymptotic distribution of H _n is derived as well.If f is square integrable, then the average number of bit comparisons in triesort is nlog₂ n+0(n), and the average number of nodes in the trie is 0(n).Research of the author was supported in part by FCAC Grant EQ-1678     

ILP turns 20

Inductive Logic Programming (ILP) is an area of Machine Learning which has now reached its twentieth year. Using the analogy of a human biography this paper recalls the development of the subject from its infancy through childhood and teenage years. We show how in each phase ILP has been characterised by an attempt to extend theory and implementations in tandem with the development of novel and challenging real-world applications. Lastly, by projection we suggest directions for research which will help the subject coming of age.     

Solving set-valued constraint satisfaction problems

In this paper, we consider the resolution of constraint satisfaction problems in the case where the variables of the problem are subsets of ${\mathbb{R}^{n}}$ . In order to use a constraint propagation approach, we introduce set intervals (named i-sets), which are sets of subsets of ${\mathbb{R}^{n}}$ with a lower bound and an upper bound with respect to the inclusion. Then, we propose basic operations for i-sets. This makes possible to build contractors that are then used by the propagation to solve problem involving sets as unknown variables. In order to illustrate the principle and the efficiency of the approach, a testcase is provided.     

A Brief Description of Gell-Mann's Lecture and How Intervals May Help to Describe Complexity in the Real World

Reliable Computing -