Javascript is not activated in your browser. This website needs javascript activated to work properly.
Du är här

Linear filtering and state space representations of hidden Markov models

Publiceringsår: 2002
Språk: Engelska
Nummer: 2002:5
Dokumenttyp: Opublicerad artikel


The topic of this paper is linear filtering of hidden Markov models (HMMs) and linear innovation form representations of HMMs. The possibility to represent the widely used HMM as a state space model is interesting in its own respect, but our interest also comes from subspace estimation methods. To be able to fit the HMM into the framework of subspace methods the process needs to be formulated in state space form. This reformulation is complicated by the non-minimality within the state space representation of the HMM. The reformulation involves deriving solutions to algebraic Riccati equations which are usually treated under minimality assumptions.



  • Mathematics and Statistics


  • ISSN: 1403-9338

Box 117, 221 00 LUND
Telefon 046-222 00 00 (växel)
Telefax 046-222 47 20
lu [at] lu [dot] se

Fakturaadress: Box 188, 221 00 LUND
Organisationsnummer: 202100-3211
Om webbplatsen