SIGNAL PROCESSING ON GRAPHS: ESTIMATING THE STRUCTURE OF A GRAPH

被引：0

作者：

Mei, Jonathan ^{[1
]}

Moura, Jose M. F. ^{[1
]}

机构：

[1] Carnegie Mellon Univ, Dept Elect & Comp Engn, Pittsburgh, PA 15213 USA

来源：

2015 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (ICASSP) | 2015年

基金：

美国国家科学基金会;

关键词：

Graph Signal Processing; Graph Structure; Adjacency Matrix; Network; Time Series; COVARIANCE ESTIMATION; MODELS;

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

This paper presents a computationally tractable algorithm for estimating the graph structure of graph signals is presented. The algorithm is demonstrated on simulated and real network time series datasets, and the performance of the new method is compared to that of related methods for estimating graph structure. The adjacency matrices estimated using the new method are shown to be close to the true graph in the simulated data and consistent with prior physical knowledge in the real dataset.

引用

页码：5495 / 5499

页数：5

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