skip to main content
Idioma:

Signal Processing on Graphs: Causal Modeling of Unstructured Data

Mei, Jonathan ; Moura, Jose M. F.

IEEE transactions on signal processing, 2017-04, Vol.65 (8), p.2077-2092 [Periódico revisado por pares]

IEEE

Texto completo disponível

Citações Citado por
  • Título:
    Signal Processing on Graphs: Causal Modeling of Unstructured Data
  • Autor: Mei, Jonathan ; Moura, Jose M. F.
  • Assuntos: adjacency matrix ; big data ; causal ; Covariance matrices ; Data models ; Graph signal processing ; graph structure ; Laplace equations ; network ; Signal processing ; Sparse matrices ; Symmetric matrices ; time series ; Time series analysis
  • É parte de: IEEE transactions on signal processing, 2017-04, Vol.65 (8), p.2077-2092
  • Descrição: Many applications collect a large number of time series, for example, the financial data of companies quoted in a stock exchange, the health care data of all patients that visit the emergency room of a hospital, or the temperature sequences continuously measured by weather stations across the US. These data are often referred to as un structured. The first task in its analytics is to derive a low dimensional representation, a graph or discrete manifold, that describes well the interrelations among the time series and their intra relations across time. This paper presents a computationally tractable algorithm for estimating this graph that structures the data. The resulting graph is directed and weighted, possibly capturing causal relations, not just reciprocal correlations as in many existing approaches in the literature. A convergence analysis is carried out. The algorithm is demonstrated on random graph datasets and real network time series datasets, and its performance is compared to that of related methods. The adjacency matrices estimated with the new method are close to the true graph in the simulated data and consistent with prior physical knowledge in the real dataset tested.
  • Editor: IEEE
  • Idioma: Inglês
Voltar para lista de resultados
Ir para página anteriorAnterior Resultado  5 AvançarIr para próxima página

  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

Buscando em bases de dados remotas. Favor aguardar.