Wavelet-Based Visual Analysis for Data Exploration

被引：7

作者：

Dal Col, Alcebiades ^{[1
]}

Valdivia, Paola ^{[1
]}

Petronetto, Fabiano ^{[2
]}

Dias, Fabio ^{[3
]}

Silva, Claudio T. ^{[3
]}

Gustavo Nonato, L. ^{[1
]}

机构：

[1] Univ Sao Paulo, Sao Paulo, Brazil

[2] Univ Fed Espirito Santo, Vitoria, ES, Spain

[3] NYU, New York, NY 10003 USA

来源：

COMPUTING IN SCIENCE & ENGINEERING | 2017年 / 19卷 / 05期

基金：

巴西圣保罗研究基金会;

关键词：

graph signal processing; scientific computing; spectral graph wavelet transforms; time-varying data;

D O I：

10.1109/MCSE.2017.3421553

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The conventional wavelet transform is widely used in image and signal processing, where a signal is decomposed into a combination of known signals. By analyzing the individual contributions, the behavior of the original signal can be inferred. In this article, the authors present an introductory overview of the extension of this theory into graphs domains. They review the graph Fourier transform and graph wavelet transforms that are based on dictionaries of graph spectral filters, namely, spectral graph wavelet transforms. Then, the main features of the graph wavelet transforms are presented using real and synthetic data. © 2017 IEEE.

引用

页码：85 / 91

页数：7

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