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Reduced-Dimension Linear Transform Coding of Correlated Signals in Networks

Publications associées (87)

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Correlation Estimation from Compressed Images

Pascal Frossard, Vijayaraghavan Thirumalai

This paper addresses the problem of correlation estimation in sets of compressed images. We consider a framework where images are represented under the form of linear measurements due to low complexity sensing or security requirements. We assume that the i ...

Elsevier2013

Privacy and Dynamics of Social Networks

Pedram Pedarsani

Over the past decade, investigations in different fields have focused on studying and understanding real networks, ranging from biological to social to technological. These networks, called complex networks, exhibit common topological features, such as a h ...

EPFL2013

Active topology inference using network coding

Christina Fragouli

Our goal, in this paper, is to infer the topology of a network when (i) we can send probes between sources and receivers at the edge of the network and (ii) intermediate nodes can perform simple network coding operations, i.e., additions. Our key intuition ...

2013

Active Testing Search for Point Cloud Matching

Pascal Fua, Raphael Sznitman, Jan Kybic, Miguel Amável Dos Santos Pinheiro

We present a general approach for solving the point-cloud matching problem for the case of mildly nonlinear transformations. Our method quickly finds a coarse approximation of the solution by exploring a reduced set of partial matches using an approach to ...

2013

3D Residual Eddy Current Field Characterisation: applied to Diffusion Weighted Magnetic Resonance Imaging

Rolf Gruetter, Alessandro Daducci, Gunnar Krüger, Kieran O'Brien, François Lazeyras

Clinical use of the Stejskal-Tanner diffusion weighted images is hampered by the geometric distortions that result from the large residual 3D eddy current field induced. In this work we aimed to predict, using linear response theory, the residual 3D eddy c ...

Institute of Electrical and Electronics Engineers2013

Beyond Moore-Penrose: Sparse Pseudoinverse

Martin Vetterli, Mihailo Kolundzija, Ivan Dokmanic

Frequently, we use the Moore-Penrose pseudoinverse (MPP) even in cases when we do not require all of its defining properties. But if the running time and the storage size are critical, we can do better. By discarding some constraints needed for the MPP, we ...

2013

Distributed Compressed Representation of Correlated Image Sets

Vijayaraghavan Thirumalai

Vision sensor networks and video cameras find widespread usage in several applications that rely on effective representation of scenes or analysis of 3D information. These systems usually acquire multiple images of the same 3D scene from different viewpoin ...

EPFL2012

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

OFDM Channel Estimation Based on Impulse Response Decimation: Analysis and Novel Algorithms

Stefano Rosati

In this paper, OFDM data-aided channel estimation based on the decimation of the Channel Impulse Response (CIR) through the selection of the Most Significant Samples (MSS) is addressed. Our aim is to approach the Minimum Mean Square Error (MMSE) channel es ...

Institute of Electrical and Electronics Engineers2012

Message-Passing De-Quantization with Applications to Compressed Sensing

Ulugbek Kamilov

Estimation of a vector from quantized linear measurements is a common problem for which simple linear techniques are suboptimal—sometimes greatly so. This paper develops message-passing de-quantization (MPDQ) algorithms for minimum mean-squared error estim ...

IEEE2012