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A current trend in marine robotics consists of performance evaluation of Unmanned Marine Vehicles (UMVs) guidance systems. This paper contributes to this by defining and testing performance indices and metrics to quantitatively measure and compare path-following performance. It focuses on the definition of a new criterion for evaluating the capability of an Unmanned Surface Vehicle (USV) to follow...
In this paper we consider the design and control of an airbreathing hypersonic vehicle. Such vehicles are characterized by non-minimum phase characteristics, instability, actuator saturation constraints, and lightly damped flexible modes.While traditional vehicle design has followed an iterative sequential procedure (with the controller design following an aero-centric vehicle design phase), an integrated...
We consider the problem of characterizing a spatial partition of the position space of a team of vehicles with double integrator kinematics. The proximity relations between the vehicles and an arbitrary target point in the partition space is the minimum control effort required for each vehicle to reach the latter point with zero miss distance and exactly zero velocity at a prescribed final time (both...
Symbolic models have recently spurred the interest of the research community because they offer a correct-by-design approach to the control of embedded and cyber-physical systems. In this paper we address construction of symbolic models for networks of discrete-time nonlinear control systems. The main result of the paper shows that under some small gain theorem-type conditions, a network of symbolic...
A good state-time quantized symbolic abstraction of an already input quantized control system would satisfy three conditions: proximity, soundness and completeness. But instability of systems, whose inputs are bounded and quantized, is an impediment to constructing fully complete state-time quantized symbolic models, even using supervisory feedback. In this paper, we come up with a way of parametrization...
Small cell networks provide an effective way to meet the explosive growth of mobile data traffic, which, however, complicates the network structure and makes intercell interference management more challenging. One existing interference management approach is to divide the whole network into disjoint clusters, with base stations (BSs) within each cluster doing interference coordination, but the performance...
In this paper, the problem of experiment design for the task of channel identification in cyclic prefixed orthogonal frequency division multiplexing (CP-OFDM) systems is revisited. So far, the optimal input sequences for least squares (LS) channel identification with respect to minimizing the channel mean square error (MSE) under an input energy constraint have been derived. Here, we investigate the...
Most evolutionary algorithms utilize the posteriori knowledge learned from the running process to guide the search. It is arguable that the priori knowledge about the problems to tackle can also play an important role in problem solving. To demonstrate the importance of both priori and posteriori knowledge, in this paper, we proposes a decomposition based estimation of distribution algorithm with...
Path planning in continuous spaces has been a central problem in robotics. In the case of systems with complex dynamics, the performance of sampling based techniques relies on identifying a good approximation to the cost-to-go distance metric. We propose a technique that uses reinforcement learning to learn this distance metric on the fly from samples and combine it with existing sampling based planners...
In this paper, we present two approximation algorithms for minimizing power consumption of wireless sensor networks (WSNs) in environmental monitoring applications. Most approximation algorithms for similar problems assume that the cost function satisfies the triangle inequality. For a cost function defined based on power consumption for reliable transmission between two nodes in a WSN, this assumption...
In many scientific fields, simulations and analyses require compositions of computational entities such as web-services, programs, and applications. In such fields, users may want various trade-offs between different qualities. Examples include: (i) performing a quick approximation vs. an accurate, but slower, experiment, (ii) using local slower execution environments vs. remote, but advanced, computing...
Publish/subscribe (pub/sub) is a popular communication paradigm in the design of large-scale distributed systems. A provider of a pub/sub service (whether centralized, peer-assisted, or based on a federated organization of cooperatively managed servers) commonly faces a fundamental challenge: given limited resources, how to maximize the satisfaction of subscribers? We provide, to the best of our knowledge,...
This paper presents an algorithm for evaluating the probability that connectivity can be maintained between two given nodes in a physical network affected by a disaster. Nodes and links in a disaster area are probabilistically broken, and the disaster area is modeled using a half plane. This paper also proves that this probability of connectivity increases for a generic network topology when the perimeter...
We consider the problem of using humans to find a bounded number of items satisfying certain properties, from a data set. For instance, we may want humans to identify a select number of travel photos from a data set of photos to display on a travel website, or a candidate set of resumes that meet certain requirements from a large pool of applicants. Since data sets can be enormous, and since monetary...
Many of today's applications can benefit from the discovery of the most central entities in real-world networks. This paper presents a new technique that efficiently finds the k most central entities in terms of closeness centrality. Instead of computing the centrality of each entity independently, our technique shares intermediate results between centrality computations. Since the cost of each centrality...
In this paper, we describe a low complexity greedy user selection scheme for multiuser MIMO systems. We propose a new metric which has significantly reduced computational complexity and improved performance compared to Frobenius norm. The approximation of projection matrix is applied to reduce the number of singular value decomposition (SVD) operations. We analyze the computational complexity of metrics,...
Worst-case design is one of the keys to practical engineering: create solutions that can withstand the most adverse possible conditions. Yet, the ever-growing need for higher energy efficiency suggest a grim outlook for worst-case design in the future. In this paper, we propose opportunistic runtime approximations to enable a continuous adaptation of the processing precision (operator type and bitwidth)...
Many applications produce acceptable results when their underlying computations are executed in an approximate manner. For such applications, approximate circuits enable hardware implementations that exhibit improved efficiency for a given quality. Previous efforts have largely focused on the design of approximate combinational logic blocks such as adders and multipliers. In practice, however, designers...
Most of the researches in feature selection deal with homogeneous features that are with either numerical or categorical features. As discussed in [2] neighbourhood rough set model is one approach which deals with heterogeneous feature selection. The neighbourhood model is used to reduce numerical and categorical features by assigning different thresholds for different kinds of attributes. Recently...
A noise-enhanced contrast stretching algorithm for enhancement of dark images in SVD-DWT domain has been presented in this paper. A dark or low-contrast image is considered to be comprising a weak signal (information) and noise (due to insufficient illumination). Since singular values of an image represent luminance of independent image layers, the internal noise may be considered to be inherent in...
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