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It has long been recognized that one of the fundamental difficulties in the estimation of two-view epipolar geometry is the capability of handling outliers. In this paper, we develop a fast and tractable algorithm that maximizes the number of inliers under the assumption of a purely translating camera. Compared to classical random sampling methods, our approach is guaranteed to compute the optimal
In some situations the closed-loop system obtained by L1 adaptive control is equivalent to linear systems. The architectures of these systems are investigated and compared with internal model control and the input observer architecture. The analysis is focused on aerospace application. An effort has been made to understand and describe what fundamental control characteristic of flying applications
Western South America is subject to considerable inter-annual variability due to El Nio-Southern Oscillation (ENSO) so forecasting inter-annual variations associated with ENSO would provide an opportunity to tailor management decisions more appropriately to the season. On one hand, the self-organizing maps (SOM) method is a suitable technique to explore the association between sea surface temperat
While only about 30% of California's usable water storage capacity lies at higher elevations, high-elevation (above 300 m) hydropower units generate, on average, 74% of California's in-state hydroelectricity. In general, high-elevation plants have small man-made reservoirs and rely mainly on snowpack. Their low built-in storage capacity is a concern with regard to climate warming. Snowmelt is expe
In this paper, we consider robust stability analysis of large-scale sparsely interconnected uncertain systems. By modeling the interconnections among the subsystems with integral quadratic constraints, we show that robust stability analysis of such systems can be performed by solving a set of sparse linear matrix inequalities. We also show that a sparse formulation of the analysis problem is equiv
This thesis investigates the topic of joint positioning and radio channel estimation and prediction. Both positioning and radio channel estimation have a long history of research with many publications but the combination of the two has so far at large been left unexplored. The reason for studying this topic is twofold: improvement of positioning and improvement of radio channel prediction. Positi
Time synchronisation is crucial for distributed systems, and particularly for Wireless Sensor Networks (WSNs), where each node is executing concurrent operations to achieve a real-time objective. However, synchronisation is quite difficult to achieve in WSNs, due to the unpredictable deployment conditions and to physical effects like thermal stress, that cause drifts in the local node clocks. As a
We propose a distributed optimization algorithm for mixed L_1/L_2-norm optimization based on accelerated gradient methods using dual decomposition. The algorithm achieves convergence rate O(1/k^2), where k is the iteration number, which significantly improves the convergence rates of existing duality-based distributed optimization algorithms that achieve O(1/k). The performance of the developed al
In manipulation tasks, motion trajectories are characterized by a set of key phases (i.e., motion primitives). It is therefore important to learn the motion primitives embedded in such tasks from a complete demonstration. In this paper, we propose a core framework that autonomously segments motion trajectories to support the learning of motion primitives. For this purpose, a set of segmentation po
At subzero temperatures, cloud particles can contain both ice and liquid water fractions. Wet growth of precipitation particles occurs when supercooled cloud liquid is accreted faster than it can freeze on impact. With a flexible framework, the theory of wet growth of hail is extended to the case of the inhomogeneities of surface temperature and of liquid coverage over the surface of the particle.
In embedded real-time systems, task priorities are often assigned to meet deadlines. However, in control tasks, a late completion of a task has no catastrophic consequence. Rather, it has a quantifiable impact in the control performance achieved by the task. In this paper, we address the problem of determining the optimal assignment of priorities and periods of sampled-data control tasks that run
An important new development within the European ENSEMBLES project has been to explore performance-based weighting of regional climate models (RCMs). Until now, although no weighting has been applied in multi-RCM analyses, one could claim that an assumption of ‘equal weight’ was implicitly adopted. At the same time, different RCMs generate different results, e.g. for various types of extremes, and
Bundle adjustment for multi-view reconstruction is traditionally done using the Levenberg-Marquardt algorithm with a direct linear solver, which is computationally very expensive. An alternative to this approach is to apply the conjugate gradients algorithm in the inner loop. Tins is appealing since the main computational step of the CG algorithm involves only a simple matrix-vector multiplication
This work investigates the predictability of seasonal to inter-annual streamflow over several river basins in Norway through the use of multi-model ensembles. As general circulation models (GCMs) do not explicitly simulate streamflow, a statistical link is made between GCM-forecast fields generated in December and average streamflow in the melting season May-June. By using the Climate Predictabili
Particles in the atmosphere are of concern due to their toxic properties and effects on climate. In coastal areas, ship emissions can be a significant anthropogenic source. In this study we investigated the contribution from ship emissions to the total particle number and mass concentrations at a remote location. We studied the particle number concentration (12 to 490 nm in diameter), the mass con
A mathematical model of spit growth and barrier elongation adjacent to an inlet (of arbitrary width), supplied by sediment coming from longshore sediment transport, was developed based on the spit growth model proposed by Kraus (1999). The fundamental governing equation is the conservation equation for sand, where the width of the spit is assumed constant during growth. The portion of the longshor
The traditional way of controlling an industrial robot is to program it to follow desired trajectories. This approach is sufficient as long as the accuracy of the robot and the calibration of the workcell is good enough. In robotic assembly these conditions are usually not fulfilled, because of uncertainties, e.g., variability in involved parts and objects not gripped accurately. Using force contr
Classical control theory does not scale well for large systems such as power networks, traffic networks and chemical reaction networks. However, many such applications in science and engineering can be efficiently modeled using the concept of positive systems and the nonlinear counterpart monotone systems. It is therefore of great interest to see how such models can be used for control. This paper
