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Shift-map image processing is a new framework based on energy minimization over a large space of labels. The optimization utilizes -expansion moves and iterative refinement over a Gaussian pyramid. In this paper we extend the range of applications to image registration. To do this, new data and smoothness terms have to be constructed. We note a great improvement when we measure pixel similarities
In the study of distributed systems, it is of fundamental interest to understand how specifications on local components and interconnections influence global properties of the system. In this paper, we consider linear continuous time systems described by sparse matrices. Properties of interest are stability and quadratic performance specifications such as passivity and input-output gain. In partic
It has been shown that optimal controller synthesis for positive systems can be formulated as a linear program. Leveraging these results, we propose a scalable iterative algorithm for the systematic design of sparse, small gain feedback strategies that stabilize the evolutionary dynamics of a generic disease model. We achieve the desired feedback structure by augmenting the optimization problems w
The problem of resource management in a sys- tem of a-priori unknown software components executing on nondeterministic hardware is considered. The approach uses on-line parameter estimation to address uncertainties and combines this with a convex optimization-based control scheme able to handle overload situations. An algorithm to solve the optimization in real-time is presented together with perf
This paper presents a reinforcement learning algorithm and provides conditions for global convergence to Nash equilibria. For several reinforcement learning schemes, including the ones proposed here, excluding convergence to action profiles which are not Nash equilibria may not be trivial, unless the step-size sequence is appropriately tailored to the specifics of the game. In this paper, we sides
We consider a networked control system where a linear time-invariant (LTI) plant, subject to a stochastic disturbance, is controlled over a communication channel with colored noise and a signal-to-noise ratio (SNR) constraint. The controller is based on output feedback and consists of an encoder that measures the plant output and transmits over the channel, and a decoder that receives the channel
Managing the resources of a virtualized data-center is a key issue in cloud computing. Existing research mostly assumes that applications are either allocated the required resources or fail. Combined with the fact that most cloud applications have dynamic resource requirements, this imposes a fundamental limitation to cloud computing: To guarantee on-demand resource allocations, the data-center ne
Traditionally, control loops are closed using periodic sensing and actuation. When communication resources are scarce, however, much may be gained from transmitting only when something important has happened in the loop. This paper presents a simple model of the interference between event-based control loops caused by sharing a common medium, based on the coupled dynamics of a Markov chain represe
The design of a controller for glycemia regulation, either in open or in closed-‐loop, relies on models able to describe the effects of a meal intake and an insulin injection on blood glucose dynamics. The purpose of this study was therefore to propose a physiological relevant yet parsimonious model for carbohydrate action on fasting blood glucose in T1DM patients when no insulin is taken.
A number of techniques have been proposed to provide run- time performance guarantees while minimizing power consumption. One drawback of existing approaches is that they work only on a fixed set of components (or actuators) that must be specified at design time. If new components become available, these management systems must be redesigned and reimplemented. In this paper, we propose PTRADE, a n
An extended Kalman-Yakubovich-Popov (KYP) Lemma for positive systems is derived. The main difference compared to earlier versions is that non-strict inequalities are treated. Matrix assumptions are also less restrictive. Moreover, a new equivalence is introduced in terms of linear programming rather than semi-definite programming. As a complement to the KYP lemma, it is also proved that a symmetri
As farms are getting bigger with more animals, less manual supervision and attention can be given the animals on both group and individual level. In order not to jeopardize animal welfare, automated supervision is in some way already in use. Function and control of ventilation is already in use in modern pig stables, e.g. by the use of sensors for temperature, relative humidity and malfunction con
In this paper a distributed version of the Kalman filter is proposed. In particular, the estimation problem is reduced to the optimization of a cost function that depends on the system dynamics and the latest output measurements and state estimates which is distributed among the agents by means of dual decomposition. The techniques presented in the paper are applied to estimate the position of mob
An adaptive resource management system combined with a thermal controller is presented. The aim of the system is to dynamically allocate computing resources to applications competing for the same computing resources in such a way that the system is not overheated. The approach has been implemented on a mobile robot. Experimental results are presented showing the feasibility of the approach.
