This paper addresses finite-time stabilization and identification problems for a class of uncertain systems with unknown parameters. New finite-time control laws are constructed with a design idea based on Lyapunov fu...
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This paper addresses finite-time stabilization and identification problems for a class of uncertain systems with unknown parameters. New finite-time control laws are constructed with a design idea based on Lyapunov functions and homogeneity.
We consider improving the performance of communications over unknown channels with unknown frequency offsets. In lieu of the commonly suggested double differential (DD) modulation/detection, we consider single differe...
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We consider improving the performance of communications over unknown channels with unknown frequency offsets. In lieu of the commonly suggested double differential (DD) modulation/detection, we consider single differential (SD) modulation/detection. We propose an approach that first estimates and compensates for the frequency offset and then detects using an existing multiple symbol detector for SD modulation. We introduce a simple data-symbol-independent frequency offset estimation method, which is reasonably accurate when using a data block larger than the one used for detection. Simulation results show that the SD modulation/detection approach proposed herein can significantly outperform the DD modulation/detection schemes.
Conditions on input signals are derived that characterize their probing richness for system identification using binary-valued observations. Identification configurations in open-loop, filtering, and feedback systems ...
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Conditions on input signals are derived that characterize their probing richness for system identification using binary-valued observations. Identification configurations in open-loop, filtering, and feedback systems are discussed together with different scenarios of noises including actuator noise, input measurement noise, and output measurement noises. In addition to system parameter estimation, identifiability and sufficient excitation conditions are also derived under unknown threshold and noise distributions
This paper proposes a novel threshold control approach for creating multi-scroll chaotic attractors. The general jerk circuit is used as an example to show the working principle of this method. The controlled jerk cir...
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This paper proposes a novel threshold control approach for creating multi-scroll chaotic attractors. The general jerk circuit is used as an example to show the working principle of this method. The controlled jerk circuit can emerge various limit cycles and n-scroll chaotic attractors by adjusting the upper threshold, lower threshold, and the width of inner saturated plateau. The dynamical mechanism of the threshold control is then further explored by analyzing the system dynamical behaviors. In particular, this method is effective and simple to implement since we only need monitor a single state variable and reset it if it exceeds the thresholds. It indicates the potential engineering applications for various chaos-based information systems
We propose an image formation algorithm for ultrasound imaging based on sparsity-driven regularization functionals. We consider data collected by synthetic transducer arrays, with the primary motivating application be...
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We propose an image formation algorithm for ultrasound imaging based on sparsity-driven regularization functionals. We consider data collected by synthetic transducer arrays, with the primary motivating application being nondestructive evaluation. Our framework involves the use of a physical optics-based forward model of the observation process; the formulation of an optimization problem for image formation; and the solution of that problem through efficient numerical algorithms. Our sparsity-driven, model-based approach achieves the preservation of physical features while suppressing spurious artifacts. It also provides robust reconstructions in the case of sparse observation apertures. We demonstrate the effectiveness of our imaging strategy on real ultrasound data
This modeling study investigates the functional role of pacemaker neurons in generating stable rhythms in the pre-Botzinger complex, a subcircuit of the respiratory pattern-generating circuitry in mammals. While the p...
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This modeling study investigates the functional role of pacemaker neurons in generating stable rhythms in the pre-Botzinger complex, a subcircuit of the respiratory pattern-generating circuitry in mammals. While the presence of pacemakers within the network is without doubt, the percentage and significance of such pacemakers is still unresolved. Here we revisited earlier network simulations by varying the fraction of pacemaker and non-pacemaker neurons within the network, and quantifying the robustness of the input parameter space and range of frequencies output by the network. Stable network rhythms were possible even with no pacemakers. However, we found that a network of at least 50% pacemakers produced the greatest range of output frequencies and had the more robust input space
Why is the optical network to date not as successful commercially as many previously thought it would be and what can the research community do to help? The author offers his opinion on this question. When one gives t...
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Why is the optical network to date not as successful commercially as many previously thought it would be and what can the research community do to help? The author offers his opinion on this question. When one gives the first part of this question some thought, several possibilities naturally come to mind: has the cause been substandard optical network performance? Have venture capitalists and entrepreneurs killed the market with glut by miscalculating and overbuilding the core? In my view, both contributed to the problem, but mostly, it is that optical networks have been engineered with insufficient attention given to the cost incurred by the end-user.
The advent of network coding has blurred the line between compression and routing in networks. In this talk, we overview the main principles of network coding and discuss the applicability of network coding to wireles...
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The advent of network coding has blurred the line between compression and routing in networks. In this talk, we overview the main principles of network coding and discuss the applicability of network coding to wireless network settings. In particular, we argue that the ablity to construct both network codes and minimum-cost subgraphs in a completely distributed fashion may provide considerable improvements, in performance and in ease of network management, over current routing-based approaches.
With high-speed space optical crosslinks, an optical satellite network as part of a larger integrated space-terrestrial network is now feasible. This radical technology building block can have profound transforming ef...
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Given a directed graphical model with binary-valued hidden nodes and real-valued noisy observations, consider deciding upon the maximum a-posteriori (MAP) or the maximum posterior-marginal (MPM) assignment under the r...
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ISBN:
(纸本)9780262232531
Given a directed graphical model with binary-valued hidden nodes and real-valued noisy observations, consider deciding upon the maximum a-posteriori (MAP) or the maximum posterior-marginal (MPM) assignment under the restriction that each node broadcasts only to its children exactly one single-bit message. We present a variational formulation, viewing the processing rules local to all nodes as degrees-of-freedom, that minimizes the loss in expected (MAP or MPM) performance subject to such online communication constraints. The approach leads to a novel message-passing algorithm to be executed offline, or before observations are realized, which mitigates the performance loss by iteratively coupling all rules in a manner implicitly driven by global statistics. We also provide (i) illustrative examples, (ii) assumptions that guarantee convergence and efficiency and (iii) connections to active research areas.
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