An efficient algorithm for dempster's completion of block-circulant covariance matrices

Francesca P. Carli, Augusto Ferrante, Michele Pavon, Giorgio Picci

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The present paper deals with maximum entropy completion of partially specified banded block-circulant matrices. This problem has many applications in signal processing since circulants happen to be covariance matrices of stationary periodic processes and maximum entropy completion (i.e. the completion which has maximal determinant) is in fact maximum likelihood estimation subject to conditional independence constraints. Moreover, the maximal determinant completion has the meaning of covariance matrix of stationary reciprocal processes ([18], [20], [21]), a class of stochastic processes which extends Markov processes and is particularly useful for modeling signals indexed by space instead of time (think for example of an image). The maximum entropy completion problem for circulant matrices has been solved in [5] and some generalizations are brougth forth in [6]. The main contribution of this paper is an efficient algorithm for its solution.

Original languageEnglish (US)
Title of host publication2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2963-2968
Number of pages6
ISBN (Print)9781612848006
DOIs
StatePublished - 2011
Event2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011 - Orlando, FL, United States
Duration: Dec 12 2011Dec 15 2011

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Other

Other2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
Country/TerritoryUnited States
CityOrlando, FL
Period12/12/1112/15/11

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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