Representation and smoothing of non-Gaussian Markov chains: a Kronecker-algebra based approach (Contributo in atti di convegno)

Type
Label
  • Representation and smoothing of non-Gaussian Markov chains: a Kronecker-algebra based approach (Contributo in atti di convegno) (literal)
Anno
  • 2007-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1109/ACC.2007.4282285 (literal)
Alternative label
  • Carravetta, F. (2007)
    Representation and smoothing of non-Gaussian Markov chains: a Kronecker-algebra based approach
    in American Control Conference (ACC 2007), New York City, New York, USA, July, 11 -- 13, 2007
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Carravetta, F. (literal)
Pagina inizio
  • 1039 (literal)
Pagina fine
  • 1044 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4282285&tag=1 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
  • Proceedings of the 2007 American Control Conference (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
  • publisher = American Automatic Control Council (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 5 (literal)
Note
  • Google Scholar (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Istituto di Analisi dei Sistemi ed Informatica (IASI) \"Antonio Ruberti\", Consiglio Nazionale delle Ricerche, Viale Manzoni 30, 00185, Roma, Italy (literal)
Titolo
  • Representation and smoothing of non-Gaussian Markov chains: a Kronecker-algebra based approach (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 1-4244-0989-6 (literal)
Abstract
  • In the present paper the class of finite-states, non- Gaussian, Markov-chains over a finite interval are considered. Under the hypothesis of complete knowledge of the process- statistics, and a nonsingularity assumption, the following results are proven: first by augmenting the process with all its Kronecker powers up to a certain degree (depending of the number of states) the augmented process can be stochastically realized by an ordinary stochastic recursive equation. Second, by supposing the process is partially and noisy observed by a linear equation, a smoothing algorithm is derived giving a smoothing estimate of the process which is optimal in a class of observation's polynomial. (literal)
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