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This article deals with the use of optimal lattice and optimal window in Discrete Gabor Transform computation. In the case of a generalized Gaussian window, extending earlier contributions, we introduce an additional local window adaptation technique for n ...
Ieee2016
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Graphs are now ubiquitous in almost every field of research. Recently, new research areas devoted to the analysis of graphs and data associated to their vertices have emerged. Focusing on dynamical processes, we propose a fast, robust and scalable framewor ...
Visual short-term memory binding tasks are a promising early marker for Alzheimer's disease (AD). To uncover functional deficits of AD in these tasks it is meaningful to first study unimpaired brain function. Electroencephalogram recordings were obtained f ...
A method to extract patterns of activity from time series of data structured as a network of objects, the method comprising the steps of creating a base graph of similar or related items from a given corpus by comparing intrinsic features of the items, com ...
2017
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One of the key challenges in the area of signal processing on graphs is to design dictionaries and transform methods to identify and exploit structure in signals on weighted graphs. To do so, we need to account for the intrinsic geometric structure of the ...
Academic Press Inc Elsevier Science2016
This paper is the first one in a series of two articles in which we revisit the optical properties of single-walled carbon nanotubes (SWNTs). Produced by rolling up a graphene sheet, SWNTs owe their intriguing properties to their cylindrical quasi-one-dime ...
Amer Inst Physics2016
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Graph Signal Processing generalizes classical signal processing to signal or data indexed by the vertices of a weighted graph. So far, the research efforts have been focused on static graph signals. However numerous applications involve graph signals evolv ...
2016
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Mining useful clusters from high dimensional data has received sig- nificant attention of the signal processing and machine learning com- munity in the recent years. Linear and non-linear dimensionality reduction has played an important role to overcome th ...
Ieee2016
The goal of this paper is to review the main trends in the domain of uncertainty principles and localization, highlight their mutual connections and investigate practical consequences. The discussion is strongly oriented towards, and motivated by signal pr ...
Springer2014
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The study of brain dynamics enables us to characterize the time-varying functional connectivity among distinct neural groups. However, current methods suffer from the absence of structural connectivity information. We propose to integrate infra-slow neural ...