2,971 research outputs found
Distributed Maximum Likelihood for Simultaneous Self-localization and Tracking in Sensor Networks
We show that the sensor self-localization problem can be cast as a static
parameter estimation problem for Hidden Markov Models and we implement fully
decentralized versions of the Recursive Maximum Likelihood and on-line
Expectation-Maximization algorithms to localize the sensor network
simultaneously with target tracking. For linear Gaussian models, our algorithms
can be implemented exactly using a distributed version of the Kalman filter and
a novel message passing algorithm. The latter allows each node to compute the
local derivatives of the likelihood or the sufficient statistics needed for
Expectation-Maximization. In the non-linear case, a solution based on local
linearization in the spirit of the Extended Kalman Filter is proposed. In
numerical examples we demonstrate that the developed algorithms are able to
learn the localization parameters.Comment: shorter version is about to appear in IEEE Transactions of Signal
Processing; 22 pages, 15 figure
A Backward Particle Interpretation of Feynman-Kac Formulae
We design a particle interpretation of Feynman-Kac measures on path spaces
based on a backward Markovian representation combined with a traditional mean
field particle interpretation of the flow of their final time marginals. In
contrast to traditional genealogical tree based models, these new particle
algorithms can be used to compute normalized additive functionals "on-the-fly"
as well as their limiting occupation measures with a given precision degree
that does not depend on the final time horizon.
We provide uniform convergence results w.r.t. the time horizon parameter as
well as functional central limit theorems and exponential concentration
estimates. We also illustrate these results in the context of computational
physics and imaginary time Schroedinger type partial differential equations,
with a special interest in the numerical approximation of the invariant measure
associated to -processes
Выделение оползневых границ по динамическим параметрам продольных преломленных волн
Дана стаття присвячена темі виділення кордонів обвального тіла за допомогою динамічних параметрів заломлених хвиль. Проведено визначення кордону двома способами: за допомогою параметра Спаського, а так само за допомогою аналізу спектрів сейсмограм. Здійснена оцінка коефіцієнта загасання сейсмічної хвилі на обвалі небезпечній ділянці.This article is dedicated to the topic selection boundaries of the landslide body by means of dynamic parameters of the refracted waves. Boundary definition is produced in two ways: by Spassky parameter, as well as by analysis of the spectra of seismograms. An assessment of the attenuation coefficient of seismic waves at the landslide site was performed
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An integrated brain-behavior model for working memory.
Working memory (WM) is a central construct in cognitive neuroscience because it comprises mechanisms of active information maintenance and cognitive control that underpin most complex cognitive behavior. Individual variation in WM has been associated with multiple behavioral and health features including demographic characteristics, cognitive and physical traits and lifestyle choices. In this context, we used sparse canonical correlation analyses (sCCAs) to determine the covariation between brain imaging metrics of WM-network activation and connectivity and nonimaging measures relating to sensorimotor processing, affective and nonaffective cognition, mental health and personality, physical health and lifestyle choices derived from 823 healthy participants derived from the Human Connectome Project. We conducted sCCAs at two levels: a global level, testing the overall association between the entire imaging and behavioral-health data sets; and a modular level, testing associations between subsets of the two data sets. The behavioral-health and neuroimaging data sets showed significant interdependency. Variables with positive correlation to the neuroimaging variate represented higher physical endurance and fluid intelligence as well as better function in multiple higher-order cognitive domains. Negatively correlated variables represented indicators of suboptimal cardiovascular and metabolic control and lifestyle choices such as alcohol and nicotine use. These results underscore the importance of accounting for behavioral-health factors in neuroimaging studies of WM and provide a neuroscience-informed framework for personalized and public health interventions to promote and maintain the integrity of the WM network
Forest resampling for distributed sequential Monte Carlo
This paper brings explicit considerations of distributed computing
architectures and data structures into the rigorous design of Sequential Monte
Carlo (SMC) methods. A theoretical result established recently by the authors
shows that adapting interaction between particles to suitably control the
Effective Sample Size (ESS) is sufficient to guarantee stability of SMC
algorithms. Our objective is to leverage this result and devise algorithms
which are thus guaranteed to work well in a distributed setting. We make three
main contributions to achieve this. Firstly, we study mathematical properties
of the ESS as a function of matrices and graphs that parameterize the
interaction amongst particles. Secondly, we show how these graphs can be
induced by tree data structures which model the logical network topology of an
abstract distributed computing environment. Thirdly, we present efficient
distributed algorithms that achieve the desired ESS control, perform resampling
and operate on forests associated with these trees
Nonequilibrium Reweighting on the Driven Diffusive Lattice Gas
The nonequilibrium reweighting technique, which was recently developed by the
present authors, is used for the study of the nonequilibrium steady states. The
renewed formulation of the nonequlibrium reweighting enables us to use the very
efficient multi-spin coding. We apply the nonequilibrium reweighting to the
driven diffusive lattice gas model. Combining with the dynamical finite-size
scaling theory, we estimate the critical temperature Tc and the dynamical
exponent z. We also argue that this technique has an interesting feature that
enables explicit calculation of derivatives of thermodynamic quantities without
resorting to numerical differences.Comment: Accepted for publication in J. Phys. A (Lett.
Nucleotide substrate binding characterization in human pancreatic-type ribonucleases.
International audienceHuman genome contains a group of more than a dozen similar genes with diverse biological functions including antiviral, antibacterial and angiogenesis activities. The characterized gene products of this group show significant sequence similarity and a common structural fold associated with binding and cleavage of ribonucleic acid (RNA) substrates. Therefore, these proteins have been categorized as members of human pancreatic-type ribonucleases (hRNases). hRNases differ in cell/tissue localization and display distinct substrate binding preferences and a wide range of ribonucleolytic catalytic efficiencies. Limited information is available about structural and dynamical properties that influence this diversity among these homologous RNases. Here, we use computer simulations to characterize substrate interactions, electrostatics and dynamical properties of hRNases 1-7 associated with binding to two nucleotide substrates (ACAC and AUAU). Results indicate that even with complete conservation of active-site catalytic triad associated with ribonucleolytic activity, these enzymes show significant differences in substrate interactions. Detailed characterization suggests that in addition to binding site electrostatic and van der Waals interactions, dynamics of distal regions may also play a role in binding. Another key insight is that a small difference in temperature of 300 K (used in experimental studies) and 310 K (physiological temperature) shows significant changes in enzyme-substrate interactions
26Al-26Mg and stable isotopes investigated in ureilites
第6回極域科学シンポジウム[OA] 南極隕石11月17日(火) 国立国語研究所 2階 講
Intérêt d’une rééducation passive pendant les 45 premiers jours après réparation de la coiffe des rotateurs
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