1,721,040 research outputs found
Robust graph signal processing in the presence of uncertainties on graph topology
No full textIn this paper we address the problem of analyzing signals defined over graphs whose topology is known only with some uncertainty about the presence/absence of some edges. This situation arises in all cases where edges are associated to a set of elements (vertices), but the association rule may be affected by errors. Building on a small perturbation analysis of the graph Laplacian matrix and assuming a simple probabilistic model for the addition/deletion of edges, we derive an analytical model to deal with the perturbation that this uncertainty induces on the observed signal. Using this model, we propose different strategies to recover the underlying signal exploiting statistical knowledge about the probability of the presence/absence of the edges1
Learning from signals defined over simplicity complexes
No full textIn the last years, several new tools have been devised to analyze signals defined over the vertices of a graph, i.e., over a discrete domain whose structure is described by pairwise relations. In this paper, we expand these tools to the analysis of signals defined on simplicial complexes, whose domain has a structure specified by various multi-way relations. Within this framework, we show how to filter signals and how to reconstruct edge and vertex signals from a subset of observations. Finally, we propose two alternative algorithms to infer the structure of the simplicial complex from the observations
Small perturbation analysis of network topologies
No full textThe goal of this paper is to derive a small perturbation analysis for networks subject to random changes of a small number of edges. Small perturbation theory allows us to derive, albeit approximate, closed form expressions that make possible the theoretical statistical characterization of the network topology changes. The analysis is instrumental to formulate a graph-based optimization algorithm, which is robust against edge failures. In particular, we focus on the optimal allocation of the overall transmit powers in wireless communication networks subject to fading, aimed at minimizing the variation of the network connectivity, subject to a constraint on the overall power necessary to maintain network connectivity
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Online recovery of time-varying signals defined over dynamic graphs
No full textThe goal of this work is to devise least mean square (LMS) strategies for online recovery of time-varying signals defined over dynamic graphs, which are observed over a (randomly) time-varying subset of vertices. We also derive a mean-square analysis illustrating the effect of graph variations and sampling on the reconstruction performance. Finally, an optimization strategy is developed in order to design the sampling probability at each node in the graph, with the aim of finding the best tradeoff between steady-state performance, graph sampling rate, and learning rate of the proposed method. Numerical simulations carried out over both synthetic and real data illustrate the good performance of the proposed learning strategies
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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