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Remote Source Coding Under Gaussian Noise: Dueling Roles of Power and Entropy Power

Related publications (38)

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A New Entropy Power Inequality for Integer-Valued Random Variables

Emmanuel Abbé, Saeid Haghighatshoar

The entropy power inequality (EPI) yields lower bounds on the differential entropy of the sum of two independent real-valued random variables in terms of the individual entropies. Versions of the EPI for discrete random variables have been obtained for spe ...

Institute of Electrical and Electronics Engineers2014

Estimation of Space-Time Varying Parameters Using a Diffusion LMS Algorithm

Ali H. Sayed

We study the problem of distributed adaptive estimation over networks where nodes cooperate to estimate physical parameters that can vary over both space and time domains. We use a set of basis functions to characterize the space-varying nature of the para ...

2014

Population Synthesis: A Different Perspective

Michel Bierlaire, Bilal Farooq

Microsimulation of urban systems evolution requires synthetic population as a key input. Currently, the focus is on treating synthesis as a fitting problem and thus various techniques have been developed, including Iterative Proportional Fitting (IPF) and ...

2013

Rate Distortion Behavior of Sparse Sources

Martin Vetterli

The rate distortion behavior of sparse memoryless sources is studied. These serve as models of sparse signal representations and facilitate the performance analysis of "sparsifying" transforms like the wavelet transform and nonlinear approximation schemes. ...

Institute of Electrical and Electronics Engineers2012

Hierarchical wavelet modelling of environmental sensor data

Anthony Christopher Davison, Yann Ruffieux

Motivated by the need to smooth and to summarize multiple simultaneous time series arising from networks of environmental monitors, we propose a hierarchical wavelet model for which estimation of hyperparameters can be performed by marginal maximum likelih ...

2011

Diffusion Bias-Compensated RLS Estimation Over Adaptive Networks

Ali H. Sayed

We study the problem of distributed least-squares estimation over ad hoc adaptive networks, where the nodes have a common objective to estimate and track a parameter vector. We consider the case where there is stationary additive colored noise on both the ...

IEEE2011

A tight bound on the performance of a minimal-delay joint source-channel coding scheme

Bixio Rimoldi, Marius Kleiner

An analog source is to be transmitted across a Gaussian channel in more than one channel use per source symbol. This paper derives a lower bound on the asymptotic mean squared error for a strategy that consists of repeatedly quantizing the source, transmit ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2010

Recursive Implementation of the Distributed Karhunen-Loeve Transform

Michael Christoph Gastpar

In the distributed linear source coding problem, a set of distributed sensors observe subsets of a data vector with noise, and provide the fusion center linearly encoded data. The goal is to determine the encoding matrix of each sensor such that the fusion ...

2010

Distributed Karhunen-Loeve Transform With Nested Subspaces

Michael Christoph Gastpar, Naveen Goela

A network in which sensors observe a common Gaussian source is analyzed. Using a fixed linear transform, each sensor compresses its high-dimensional observation into a low-dimensional representation. The latter is provided to a central decoder that reconst ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2009

SURE-Based Non-Local Means

Dimitri Nestor Alice Van De Ville, Michel Kocher

Non-local means (NLM) provides a powerful framework for denoising. However, there are a few parameters of the algorithm-most notably, the width of the smoothing kernel-that are data-dependent and difficult to tune. Here, we propose to use Stein's unbiased ...

Institute of Electrical and Electronics Engineers2009