Causality and Information Dynamics in Networked Systems with Many Agents

Abstract

This report presents results on a theoretical formulation and algorithms for reconstructing Granger causality graphs (GCG) from collections of wide sense stationary (WSS) and cyclostationary time series data. The thrust of the research was to develop methods for GCG sparsification using ideas from Tikhonov regularization and ADMM based proximal algorithms. Several computational examples are presented.

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Document Details

Document Type
Technical Report
Publication Date
May 11, 2017
Accession Number
AD1051320

Entities

People

  • Ravi R. Mazumdar

Organizations

  • University of Waterloo

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Coefficients
  • Computational Science
  • Computations
  • Covariance
  • Electronic Mail
  • Equations
  • Errors
  • Estimators
  • Filters
  • Graphs
  • Hilbert Space
  • Markov Processes
  • Random Variables
  • Sequences
  • Standards
  • Stochastic Processes

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Distributed Systems and Data Platform Development
  • Statistical inference.