Recursive Optimal Smoothing for Finite State Hidden Reciprocal Processes (Articolo in rivista)

Type
Label
  • Recursive Optimal Smoothing for Finite State Hidden Reciprocal Processes (Articolo in rivista) (literal)
Anno
  • 2011-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1109/TAC.2011.2141510 (literal)
Alternative label
  • White, L.B.; Carravetta, F. (2011)
    Recursive Optimal Smoothing for Finite State Hidden Reciprocal Processes
    in IEEE transactions on automatic control (Print); IEEE, Institute of electrical and electronics engineers, New York (Stati Uniti d'America)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • White, L.B.; Carravetta, F. (literal)
Pagina inizio
  • 2156 (literal)
Pagina fine
  • 2161 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.nd.edu/~ieeetac/ (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 56 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
  • Rapporto di Ricerca IASI-CNR N. 11-2 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 5 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 9 (literal)
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • L. B. White, School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide 5067, Australia (e-mail: lang.white@adelaide. edu.au). F. Carravetta, Insituto di Analisi dei Sistemi ed Informatica \"An- tonio Ruberti,\" Consiglio Nazionale della Ricerche, Roms 00185, Italy (e-mail: francesco.carravetta@iasi.cnr.it). (literal)
Titolo
  • Recursive Optimal Smoothing for Finite State Hidden Reciprocal Processes (literal)
Abstract
  • This technical note addresses modelling and estimation of a class of finite state random processes called hidden reciprocal chains (HRC). A hidden reciprocal chain consists of a finite state reciprocal process, together with an observation process conditioned on the recip- rocal process much as in the case of a hidden Markov model (HMM). The key difference between Markov models and reciprocal models is that reciprocal models are non-causal. The technical note presents a characterization of a HRC by a finite set of hidden Markov bridges, which are HMMs with the final state fixed. The technical note then uses this characterization to derive the optimal fixed interval smoother for a HRC. Performance of linear and optimal smoothers derived for both HMM and HRC are compared (using simulations) for a class of HRC derived (literal)
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