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This paper focuses on distributed state estimation using a sensor network for monitoring a linear system. In order to account for physical constraints on process states and inputs, we propose a moving horizon approach where each sensor has to solve a quadr ...
We show how variational Bayesian inference can be implemented for very large binary classification generalized linear models. Our relaxation is shown to be a convex problem for any log-concave model, and we provide an efficient double loop algorithm for so ...
We consider the problem of locating point sources in the planar domain from overdetermined boundary measurements of solutions of Poisson's equation. In this paper, we propose a novel technique, termed "analytic sensing," which combines the application of G ...
We use the truncated Wigner approximation to derive stochastic classical field equations for the description of polariton condensates. Our equations are shown to reduce to the Boltzmann equation in the limit of low polariton density. Monte Carlo simulation ...
In recent work, we have shown that in a Gaussian network, nodes can often recover linear combinations of transmitted codewords much more efficiently than the codewords themselves. These nodes, after decoding their linear equations, simply send them towards ...
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In the context of OD matrix estimation from traffic counts, we propose a new linearization of the network loading map that is superior to the usual proportional assignment in congested conditions. ...
We discuss in this paper the numerical approximation of fluid-structure interaction (FSI) problems dealing with strong added-mass effect. We propose new semi-implicit algorithms based on inexact block-LU factorization of the linear system obtained after th ...
In this paper we use bilevel programming to find the maximum difference between a reference controller and a low-complexity controller in terms of the infinity-norm difference of their control laws. A nominal MPC for linear systems with constraints, and a ...
Abstract In the context of dynamic traffic assignment (DTA), the network loading map represents a traffic flow model. Assuming that an iterative DTA microsimulator is given, this article discusses several techniques for the linearization of the network loa ...
For a centralized encoder and decoder, a channel matrix is simply a set of linear equations that can be transformed into parallel channels. We develop a similar approach to multiuser networks: we view interference as creating linear equations of codewords ...
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