This paper studies some properties of the recently developed parametric Lyapunov equation based low gain feedback design method. As applications of these new properties, alternative and simpler solutions are proposed ...
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We propose an automatic method for the segmentation of the brain structures in three dimensional (3D) Magnetic Resonance Images (MRI). The proposed method consists of two stages. In the first stage, we represent the s...
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This paper addresses the computation of the L 2 -induced gain for a class of switched systems. The main contribution of the paper is to completely characterize the induced gain of the switched system through a system ...
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This paper addresses the computation of the L 2 -induced gain for a class of switched systems. The main contribution of the paper is to completely characterize the induced gain of the switched system through a system of differential inequalities on a common storage function, one for each system being switched. The motivation for computing the induced gain of a switched system is the application of robust stability tools to the analysis of hybrid systems.
Multicluster grids provide one promising solution to satisfying growing computation demands of compute-intensive applications by collaborating various networked clusters. However, it is challenging to seamlessly integ...
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Multicluster grids provide one promising solution to satisfying growing computation demands of compute-intensive applications by collaborating various networked clusters. However, it is challenging to seamlessly integrate all participating clusters in different domains into a virtual computation platform. In order to take full advantages of multicluster grids capability, computer scientists need to deal with how to collaborate practically and efficiently participating autonomic systems to execute Grid-enabled applications. We make efforts on grid resource management and implement a toolkit called Pelecanus to improve the overall performance of application execution in multicluster grids environment. The Pelecanus takes advantages of the DA-TC (Dynamic Assignment with Task Containers) execution model to improve resource interoperability and enhance application execution and monitoring. Experiments show that it can significantly reduce turnaround time and increase resource utilization for certain applications with large number of sequential jobs.
This paper considers the formation control problem for autonomous robots, where the target formation is specified as a minimally rigid formation. A distributed control law based on potential functions is derived from ...
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This paper considers the formation control problem for autonomous robots, where the target formation is specified as a minimally rigid formation. A distributed control law based on potential functions is derived from a directed sensor graph and relies on the graph matrices only. By methods of inverse optimality a certain class of sensor graphs is identified that is related to a cooperative behavior among the robots. These graphs are referred to as cooperative graphs, and undirected graphs, directed cycles, and directed open chain graphs can be identified as such graphs. Cooperative graphs admit a local stability result of the target formation together with a guaranteed region of attraction, that depends on the rigidity properties of the formation.
Magnetoencephalography (MEG) is a neuroimaging technique for brain activation detection. This technique does not provide a unique solution due to ill-posedness of its inverse solution. Several methods are proposed to ...
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In this paper, the information consensus filter (ICF) is adapted to non-linear process and measurement models by employing an extended information filter (EIF). The nonlinear ICF is a decentralized estimator, where ea...
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Being able to predict the coming seizure can impressively improve the quality of the patients' lives since they can be warned to avoid doing risky activities via a prediction system. Here, a locally linear neuro f...
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Being able to predict the coming seizure can impressively improve the quality of the patients' lives since they can be warned to avoid doing risky activities via a prediction system. Here, a locally linear neuro fuzzy model is used to predict the EEG time series. Subsequently, this model is utilized in accompany with Singular Spectrum Analysis for prediction. Afterward, an information theoretic criterion is used to select a reliable subset of input variables which contain more information about the target signal. Comparison of three mentioned methods on one hand shows that SSA enables our prediction model to extract the main patterns of the EEG signal and highly improves the prediction accuracy. On the other hand, applying the method of channel selection to the model yields more accurate prediction. It is shown that fusion of some certain signals provides more information about the target and considerably improves the prediction ability.
Random pulse width modulation (RPWM) technique has been employed to generate the control signals of Vienna-type rectifier. This technique is compared to two conventional techniques (Hysteresis-band and ramp comparison...
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Random pulse width modulation (RPWM) technique has been employed to generate the control signals of Vienna-type rectifier. This technique is compared to two conventional techniques (Hysteresis-band and ramp comparison with fix frequency carrier signal). Simulation results are illustrated for three approaches. The results verify significantly reduction of high frequency harmonics magnitude;and consequently overcome electromagnetic interference (EMI) problem in this active type of rectifier.
This paper addresses the problem of synchronization errors in distributed dynamical systems. In particular, it focuses on the question of stability for the case where all subsystems have the same sampling frequency, b...
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ISBN:
(纸本)9781424445233
This paper addresses the problem of synchronization errors in distributed dynamical systems. In particular, it focuses on the question of stability for the case where all subsystems have the same sampling frequency, but different switching times. In contrast to previous work, the approach taken here models the set of system matrices that arise using a polytopic uncertainty approach, where a polytope vertex corresponds to a possible state matrix of the overall system. System stabilization is then approached through state feedback and LMI techniques are used to generate the control law matrices. A method to handle the combinatorial explosion of the number of polytope vertices is developed and illustrated using an example from swarm system navigation.
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