Publication

Estimating target state distributions in a distributed sensor network using a Monte-Carlo approach

Related publications (38)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Compromise Pitman estimators

Nicolas Fournier

In this paper, we investigate the construction of compromise estimators of location and scale, by averaging over several models selected among a specified large set of possible models. The weight given to each distribution is based on the profile likelihoo ...

Elsevier2011

Dynamic network loading: a differentiable model that derives link state distributions

Michel Bierlaire, Gunnar Flötteröd, Carolina Osorio Pizano

We present a dynamic network loading model that yields queue length distributions, accounts for spillbacks, and maintains a differentiable mapping from the dynamic demand on the dynamic queue lengths. The approach builds upon an existing stationary queuein ...

2010

Benford's Law and Its Application to Lightning Data

Marcos Rubinstein, Wolfgang Schulz, Pooyan Manoochehrnia

Benford's law applies to a wide variety of natural and man-made datasets and it has been successfully applied to test the integrity of data and to detect possible fraud and anomalous results in economy, politics, and management studies. In this paper, we i ...

2010

Alternative(s) to fractional-diffusion equations in bedload transport models.

Christophe Ancey, François Mettra, Valentin Métraux

The idea of stochastic sediment transport models emerged in the 1930s, notably with the doctoral work of Hans A. Einstein (1936). Einstein's seminal work gave impulse to several stochastic models, which usually led to thin-tailed or bounded distributions f ...

2010

Statistical analysis of clusters of extreme events

Mária Süveges

The thesis is a contribution to extreme-value statistics, more precisely to the estimation of clustering characteristics of extreme values. One summary measure of the tendency to form groups is the inverse average cluster size. In extreme-value context, th ...

EPFL2009

A MAP Approach to Noise Compensation of Speech

Philip Neil Garner

We show that estimation of parameters for the popular Gaussian model of speech in noise can be regularised in a Bayesian sense by use of simple prior distributions. For two example prior distributions, we show that the marginal distribution of the uncorrup ...

Idiap2009

Learning with Compressible Priors

Volkan Cevher

We describe a set of probability distributions, dubbed compressible priors, whose independent and identically distributed (iid) realizations result in p-compressible signals. A signal x in R^N is called p-compressible with magnitude R if its sorted coeffic ...

2009

The role of silver on the stabilization of the incommensurately modulated structure in calaverite, AuTe2

Gervais Chapuis, Alla Arakcheeva

Structural investigations of several minerals belonging to the calaverite group with composition Au1–xAgxTe2 (x = 0.00, 0.02, 0.05, 0.09, 0.19, and 0.33) indicate that Ag is randomly distributed on the Au sites. This suppresses the valence fluctuation of A ...

Mineralogical Society of America2009

Decentralized State Initialization with Delay Compensation for Multi-modal Sensor Networks

Volkan Cevher

Decentralized processing algorithms are attractive alternatives to centralized algorithms for target tracking applications in smart sensor networks since they provide the ability to scale, reduce vulnerability, reduce communication and share processing res ...

Springer Verlag2007

Low computation and low latency algorithms for distributed sensor network initialization

Volkan Cevher

In this paper, we show how an underlying system’s state vector distribution can be determined in a distributed heterogeneous sensor network with reduced subspace observability at the individual nodes. The presented algorithm can generate the initial state ...

Springer Verlag2007