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Vertex-Frequency Analysis on Graphs

Publications associées (36)

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A Unifying Parametric Framework for 2D Steerable Wavelet Transforms

Michaël Unser

We introduce a complete parameterization of the family of two-dimensional steerable wavelets that are polar-separable in the Fourier domain under the constraint of self-reversibility. These wavelets are constructed by multiorder generalized Riesz transform ...

Siam Publications2013

On the Sparsity of Wavelet Coefficients for Signals on Graphs

Pierre Vandergheynst, Benjamin Ricaud, David Shuman

A number of new localized, multiscale transforms have recently been introduced to analyze data residing on weighted graphs. In signal processing tasks such as regularization and compression, much of the power of classical wavelets on the real line is deriv ...

Spie-Int Soc Optical Engineering2013

A Windowed Graph Fourier Transform

Pierre Vandergheynst, Benjamin Ricaud, David Shuman

The prevalence of signals on weighted graphs is increasing; however, because of the irregular structure of weighted graphs, classical signal processing techniques cannot be directly applied to signals on graphs. In this paper, we define generalized transla ...

Ieee2012

A Windowed Graph Fourier Transform

Pierre Vandergheynst, Benjamin Ricaud, David Shuman

IEEE2012

On localisation and uncertainty measures on graphs

Nathanaël Perraudin

Due to the appearance of data on networks such as internet or Facebook, the number of applications of signal on weighted graph is increasing. Unfortunately, because of the irregular structure of this data, classical signal processing techniques are not app ...

2012

Formation preserving path finding in 3-D terrains

Ali Galip Bayrak

Navigation of a group of autonomous agents that are required to maintain a formation is a challenging task which has not been studied much especially in 3-D terrains. This paper presents a novel approach to collision free path finding of multiple agents pr ...

Springer Verlag2012

Chebyshev polynomial approximation for transductive learning on graphs

Nathanaël Perraudin

The goal of transductive learning is to find a way to recover the labels of lots of data with only a few known samples. In this work, we will work on graphs for two reasons. First, it’s possible to construct a graph from a given dataset with features. The ...

2011

On-line frequency adaptation and movement imitation for rhythmic robotic tasks

Auke Ijspeert, Tadej Petric

In this paper we present a novel method to obtain the basic frequency of an unknown periodic signal with an arbitrary waveform, which can work online with no additional signal processing or logical operations. The method originates from non-linear dynamica ...

2011

Signal Processing in Space and Time

Francisco Pereira Correia Pinto

Sound waves propagate through space and time by transference of energy between the particles in the medium, which vibrate according to the oscillation patterns of the waves. These vibrations can be captured by a microphone and translated into a digital sig ...

EPFL2010

Frame Domain Signal Processing: Framework and Applications

Martin Vetterli, Amina Chebira

Besides basis expansions, frames representations play a key role in signal processing. We thus consider the problem of frame domain signal processing, which is more complex and challenging than transform domain processing. Examples of such processing aboun ...

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