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A Novel Method for Sampling Bandlimited Graph Signals

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Deconvolution of Gaussian Random Fields using the Graph Fourier Transform

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Real-life acquisition systems are fundamentally limited in their ability to reproduce point sources. For example, a point source object, a star say, observed with an optical telescope is blurred by the imperfect lenses composing the system. Mathematically, ...

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In this paper, we study diffusion social learning over weakly-connected graphs. We show that the asymmetric flow of information hinders the learning abilities of certain agents regardless of their local observations. Under some circumstances that we clarif ...

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Random sampling of bandlimited signals on graphs

Pierre Vandergheynst, Rémi Gribonval, Gilles Puy, Nicolas Tremblay

We study the problem of sampling

k

-bandlimited signals on graphs. We propose two sampling strategies that consist in selecting a small subset of nodes at random. The first strategy is non-adaptive, \ie, independent of the graph structure, and its perform ...

2015

Joint Power Allocation and Path Selection for Multi-Hop Noncoherent Decode and Forward UWB Communications

Xiaoli Ma, Marco Mondelli, Qi Zhou

With the aim of extending the coverage and improving the performance of impulse radio ultra-wideband (UWB) systems, this paper focuses on developing a novel single differential encoded decode and forward (DF) non-cooperative relaying scheme (NCR). To favor ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Too much success for recent groundbreaking epigenetic experiments

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An article reporting statistical evidence for epigenetic transfer of learned behavior has important implications, if true. With random sampling, real effects do not always result in rejection of the null hypothesis, but the reported experiments were unifor ...

Genetics Society of America2014

Learning of Structured Graph Dictionaries

Pascal Frossard, Xiaowen Dong, Xue Zhang

We propose a method for learning dictionaries towards sparse approximation of signals defined on vertices of arbitrary graphs. Dictionaries are expected to describe effectively the main spatial and spectral components of the signals of interest, so that th ...

2012

Disjoint homometric sets in graphs

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Two subsets of vertices in a graph are called homometric if the multisets of distances determined by them are the same. Let h(n) denote the largest number h such that any connected graph of n vertices contains two disjoint homometric subsets of size h. It ...

2011

Fast Computation of Small Cuts via Cycle Space Sampling

David Pritchard

We describe a new sampling-based method to determine cuts in an undirected graph. For a graph (V, E), its cycle space is the family of all subsets of E that have even degree at each vertex. We prove that with high probability, sampling the cycle space iden ...

2011

Information Processing and Structure of Dynamical Networks

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Networks are everywhere and we are confronted with many networks in our daily life. Networks such as Internet, World Wide Web, social, biological and economical networks have been subject to extensive studies in the last decade. The volume of publications ...

EPFL2011

The impact of mobility on the time complexity for deterministic broadcasting in radio networks

André Schiper, David Cavin, Yoav Sasson

We study the time complexity for deterministic broadcasting algorithms in mobile radio networks. The broadcast operation consists of a source node successfully communicating its message to every other node. In multi-hop radio networks such as MANETs, the m ...

2011

Random sampling of bandlimited signals on graphs

Pierre Vandergheynst, Rémi Gribonval, Gilles Puy, Nicolas Tremblay

We study the problem of sampling

k

2015